Criminal record analysis to support the European Pact on International Drug Trafficking (EPDT)
Supported by the Criminal Justice Programme of the European Union
ACRO Criminal Records Office Supported by the Criminal Justice Programme of the European Union
This publication has been produced with the financial support of the Criminal Justice Programme of the European Union. The contents of this publication are the sole responsibility of the ACRO Criminal Records Office (ACRO) and can in no way be taken to reflect the views of the European Commission.
Author: Jo Jackson, ACRO Intelligence Analyst Project support: Andrew Linton, ACRO Project Support Officer 1 Acknowledgements
1.1 The project team would like to express our gratitude to everybody who contributed to the completion of the project.
Without the cooperation and input from the following persons it would not have been possible to collate the data for analysis.
Spain Croatia Alfredo Sanchez de Dios, Darko Vincek Diego Aguilar Nina Zecic Petra Mise Lithuania Donatas Valiukas, Germany Lina Svisciauskaite Peter Stenzel Viktorija Pranke Verena Muehlenbeck
Romania Liliana Pasare Hungary Mihai Bobescu Gabriella Borza Veronika Berta Belgium Stefanie Van Assche Italy Laurent Sobrie Daniela Piccioni Tom Kielemoes Tuur De Bock Vincent Cambier
1.2 The project team would also like to thank the following for their support and assistance throughout the duration of the project.
Project board members: Non project board members:
Adrian Hudson Claire Wills Service Delivery Manager, Hampshire Constabulay Head of Section - ECRIS, ACRO
Anna Richardson Dawn Bell Drugs and Alcohol Research Team, Finance Officer, ACRO Crime and Policing Analysis, Home Office Danny Jordan Jon Hudson PNC Services, Home Office Senior Manager, Intelligence and Operations Directorate, National Crime Agency (NCA) Gemma Wooldridge Graphic Designer, ACRO Ken Littlewood Project Executive, ACRO Julia Barnard IT Manager, ACRO Mike Scott Intelligence Manager, ACRO Paul Moorman Senior Intelligence Analyst, ACRO Stephen Vitkovitch Deputy Head, International Criminality Unit, Sean de Fraine Home Office IT Technical Delivery Manager, ACRO
Tim Feltham Head of Communications, ACRO acro.police.uk 3 2 Acronyms and abbreviations
ACRO ACRO Criminal Records Office CFD Council Framework Decision ECRIS European Criminal Records Information System EEA European Economic Area EMCDDA European Monitoring Centre for Drugs and Drug Addiction EMPACT European Multidisciplinary Platform Against Criminal Threats EPDT European Pact on Drugs Trafficking EU European Union FNO Foreign National Offender(s) GSA Geoff Smith Associates ICCE International Criminal Conviction Exchange INCSR International Narcotics Control Strategy Report IT Information Technology M.O. Modus Operandi MOJ Ministry of Justice MS Member State(s) NCA National Crime Agency NEU-ECR Non-European Union Exhange of Criminal Records NI Notifications In NJR Network of Judicial Registers NO Notifications Out NPCC National Police Chiefs Council NPS New Psychoactive Substances OCG Organised Crime Group(s) PID Project Initiation Document PNC Police National Computer QUEST Query Using Extended Search Techniques SOCTA Serious and Organised Crime Threat Assesment SPOC Single Point Of Contact UK United Kingdom UKCA-ECR UK Central Authority for the Exchange of Criminal Records USA United States of America
Connection matrix country abbreviations
AT Austria IT Italy BE Belgium LV Latvia BG Bulgaria LT Lithuania HR Croatia LU Luxembourg CY Cyprus MT Malta CZ Czech NL Netherlands DK Denmark PL Poland EE Estonia PT Portugal FI Finland RO Romania FR France SK Slovakia DE Germany SI Slovenia GR Greece ES Spain HU Hungary SE Sweden IE Ireland GB United Kingdom
4 Criminal record analysis to support the European Pact on International Drug Trafficking Contents
1 Acknowledgements 3 2 Acronyms and abbreviations 4 3 Executive summary 6 4 Introduction 8 Project overview 9
5 Background 9 6 Project aim and initiation 12 7 Data sources 15 8 Member State engagement 20 9 Data acquisition, extraction an quality assurance 23 10 Data research and analysis 25 11 The IT solution 27 12 Serious and Organised Crime 29 13 Research 30 Country analysis 33 14 United Kingdom 33 15 Spain 48 16 Lithuania 57 17 Romania 64 18 Germany 66 19 Belgium 73 20 Hungary 78 21 Croatia 80 22 Italy 86
23 Key findings 88 24 Conference 93 25 Forward look 98 26 Conclusion 100 27 Recommendations 104 28 Lessons learnt 105 29 Appendices 107
acro.police.uk 5 3 Executive summary
3.1 In the EU where citizens including criminals can freely cross borders, it is essential for public safety that criminal records information is exchanged between European Union (EU) Member States (MS). As a result of this, EU Council Framework Decision 2009/315/JHA (on the organisation and content of the exchange of information extracted from the criminal records between MS) was implemented. On 27th April 2012 Council Decision 2009/316/JHA (on the establishment of a European Criminal Records Information System (ECRIS) in application of Article 11 of Framework Decision 2009/315/JHA) was implemented. ECRIS provides a secure electronic system to exchange criminal records information between MS. Since the implementation, 1,120,319 notification messages have been exchanged between MS, which includes the convictions and updates to convictions of EU nationals in MS other than their MS of nationality.
3.2 On 3rd June 2010 the Council of the EU agreed to a European pact to combat international drug trafficking, initially focussed on disrupting cocaine and heroin trafficking routes. This emanated from the current European Multidisciplinary Platform Against Criminal Threats (EMPACT) cycle and the work of Europol and the European Council.
3.3 The ACRO Criminal Records Office (ACRO), which hosts the UK Central Authority for the Exchange of Criminal Records (UKCA-ECR) identified that there was potential significant value that can be routinely derived from criminal records information held by and subsequently exchanged by EU MS. This could contribute to the fight against international drugs trafficking.
3.4 A two year project funded by the European Commission, the European Pact of Drugs Trafficking (EPDT) was established to explore the opportunities to analyse bulk criminal records data focussing on drugs offences relating to cocaine and heroin held on individual MS, ECRIS and national criminal registers. This was to evaluate how criminal records across the EU can be utilised to support an EU pact of international drugs trafficking. The project had three key objectives, in order to achieve these objectives, the activities were divided into three main work streams. These are detailed later in the report.
3.5 The project sought to conduct a large scale research project with other EU MS utilising and analysing data from ECRIS and national criminal registers from 12 MS to establish whether EU wide crime patterns emerge and whether EU law enforcement and government agencies could benefit from this information. The report also discusses the limitations of the analysis conducted as only nine MS could provide ECRIS and national criminal register data within the time frame of the project. This was due to a number of MS having considerable difficulty in providing the data requested, which related to either issues of the data not being available due to data retention guidelines or simply that the MS do not record the offences in the same manner in relation to offence type, offence location or classification of drug.
6 Criminal record analysis to support the European Pact on International Drug Trafficking 3.6 The project team reviewed the system architecture for each MS ECRIS and identified a common denominator of having Microsoft as the operating system. As a result of this the project team identified a solution compatible with the ECRIS database called Power BI. Power BI simplifies data recovery, access and collaboration and it is available at little or no cost to MS. Power BI was used extremely effectively to analyse millions of rows of data provided by MS and present these findings to delegates at the end of project conference.
3.7 The project identified that existing EU co-operation mechanisms can be enhanced by using criminal records to combat international drugs trafficking. Currently the European Monitoring Centre for Drugs and Drugs Addiction (EMCDDA) collects data from all 28 EU MS which assists in informing and designing drugs legislation and intervention strategies. However the data does not include ECRIS conviction data. Close collaboration with the EMCDDA and the EPDT project has identified that utilising ECRIS conviction data and combining it with existing EMCDDA data, a fuller picture of the scale of drugs trafficking and drugs addiction could be recognised. In addition the project team have identified that Europol could potentially benefit not only from drugs trafficking data analysed during this project but the analysis of other serious crime data held within ECRIS. Europol supports all MS by providing specific expertise, facilitating the exchange of intelligence and joint investigation teams. This support is underpinned by a multi-annual policy cycle known as EMPACT. Europol do not currently have access to ECRIS conviction data. The project team believe that the analysis of ECRIS data could enhance Europol’s ability to further develop the Serious Organised Crime Threat Assessment (SOCTA) and inform the Strategic and Operational Action Plans to combat priority threats across the EU.
acro.police.uk 7 4 Introduction
4.1 ACRO is the responsible authority on behalf of the UK for exchanging criminal records information with other EU and Non EU MS. As a policing organisation ACRO has a duty to maximise the value derived from exchanging criminal records and in this includes utilising any intelligence that can be extracted from information that it processes.
4.2 Whilst there are many tools available for understanding this area of drug trafficking, ACRO believes that there is significant value that can be derived from criminal records information which is exchanged or held by EU MS that could contribute to the fight against international drug trafficking.
4.3 EU MS have been routinely exchanging criminal records information for a number of years. ECRIS was implemented on 27th April 2012 to ensure an effective, efficient and secure way of exchanging criminals records information between MS. A number of MS achieved ‘live’ status on the 27th April and commenced exchanging criminal records through ECRIS in relation to criminal proceedings and for purposes other than criminal proceedings, whilst some countries, have still to connect to ECRIS.
4.4 The project sought to better understand how analysing bulk ECRIS criminal record data from across the EU could assist in the fight against international drug trafficking. In particular, supporting the European Pact on International Drug Trafficking.
4.5 The project had three key objectives:
a) To evaluate how criminal records across the EU can be utilised to support an EU pact on international drug trafficking.
b) To identify a model that enables analysis of criminal records to continue once the project expires.
c) To identify how existing EU cooperation mechanisms can be enhanced by using criminal records to continue once the project expires.
4.6 To achieve the project objectives and provide the deliverables, the EPDT project had three core work streams that were divided into a number of manageable stages;
Work stream one - Research and analysis to identify patterns of offending in international drug trafficking by utilising conviction data.
Work stream two - Implement an IT capability to efficiently extract offence and conviction data from ACRO systems.
Work stream three - Host an international closing event to relay the findings of the research to stakeholders.
8 Criminal record analysis to support the European Pact on International Drug Trafficking 5 Background
5.1 The UKCA-ECR was established following Council Decision 2005/876/JHA, which obligates the UK to exchange criminal conviction information with other EU MS.
5.2 Prior to the ratification of the 2005/876/JHA Council Decision, the UK received conviction notifications relating to UK nationals convicted in EU MS under the 1959 European Convention on Mutual Legal Assistance (Article 13) and had the right to respond to and send out requests for criminal conviction information under Article 22 of that European Convention.
5.3 To enable the sharing of conviction information, each EU MS was mandated to establish a Central Authority (or as defined in Network of Judicial Registers (NJR) documentation: a register) to be the focal point for internal and external communications of requests, information or notifications concerning criminal records. Within the UK, the Home Office agreed that ACRO would be responsible for hosting the UK Central Authority.
5.4 Building on Council Decision 2005/876/JHA, four EU MS commenced a NJR pilot, with a subsequent eleven MS joining at a later date – Germany, France, Spain, Belgium, Czech Republic, Luxembourg, Slovakia, UK, Poland, Slovenia and Italy. The NJR pilot looked at the facilitation of an electronic exchange of criminal conviction information through the sharing of conviction information contained in the countries’ criminal registers.
5.5 The European Commission, in the meantime, commenced the ECRIS project, which looked at the electronic exchange of criminal record information to support the aims of Council Framework Decision (CFD) 2009/315/JHA on the exchange of information from criminal records across all MS.
5.6 The electronic exchange of conviction information to the standardised ECRIS format was required within three years of the publishing of the EU Council Framework Decision 2009/315/JHA on the organisation and content of the exchange of information extracted from the criminal record between MS.
5.7 EU Framework Decision 2008/675/JHA required that criminal convictions within EU MS will be taken into account in criminal proceedings in another MS to the same extent that previous criminal convictions are taken into account that occurred within that jurisdiction. This requirement underpins the objectives of the project. If this information is being exchanged and utilised then there should be the ability to analyse this data to identify trends in criminality to identify trends in cross-national criminality.
acro.police.uk 9 5.8 CFD 2009/315/JHA has been established since April 2012. This has seen the growth in the exchange of criminal records information between 27 of the 28 MS.1 There is the potential to assist law enforcement agencies by analysing different crime types. It is on this basis that the project applied for funding to support investigating the theory in relation to narcotic crimes.
5.9 The fight against international drug trafficking within the EU continues to be a significant risk to public protection in EU MS. The importance of this threat is recognised by all MS. On the 3rd June 2010, the Council of the European Union meeting in Luxembourg, agreed to a European pact against international drug trafficking initially focussed on cocaine and heroin trafficking. This was identified as an integral part of the EU’s anti-drug strategy and for this reason it forms a major part of the coordinated response by Europol.
5.10 Europol is Europe’s law enforcement agency based in The Hague and staffed with over 900 personnel from all 28 EU MS. Europol supports all MS in many ways, specific expertise, facilitating the exchange of information, joint investigation teams etc. This support is underpinned by a multi-annual policy cycle known as EMPACT (European Multidisciplinary Platform Against Criminal Threats).
5.11 The cycle runs for four years and commenced in 2013. It consists of four key stages;
5.12 The cycle operates on a four stage basis, the first being the creation of the Serious and Organised Crime Threat Assessment (SOCTA). This assesment provided the EU Council with nine priorities for the period 2013-2017. These priorities lead to the development of Strategic Action Plans and then Operational Action Plans to combat the priority threats.
1 As of 12th September 2016, Portugal is the only MS that is not currently exchanging any conviction information with any other MS. See the connectivity matrix in Appendix A for an overview of MS connectivity.
10 Criminal record analysis to support the European Pact on International Drug Trafficking 5.13 The nine priorities are as follows;
• Facilitation of illegal immigration – aiming to: disrupt organised crime groups (OCG) involved in facilitation of illegal immigration operating in the source countries, at the main entry points to the EU on the main routes and, where evidence based, on alternative channels. To reduce OCGs’ abuse of legal channels for migration including the use of fraudulent documents as a means of facilitating illegal immigration.
• Trafficking in human beings – aiming to: disrupt OCGs involved in intra-EU human trafficking and human trafficking from the most prevalent external source countries for the purposes of labour exploitation and sexual exploitation; including those groups using legal business structures to facilitate or disguise their criminal activities.
• Counterfeit goods – aiming to: disrupt the OCGs involved in the production and distribution of counterfeit goods violating health, safety and food regulations and those producing sub-standard goods.
• Excise and Missing Trader Intra Community (MTIC) Fraud – aiming to: disrupt the capacity of OCGs and specialists involved in excise fraud and MTIC fraud.
• Synthetic drugs – aiming to: reduce the production of synthetic drugs in the EU and to disrupt the OCGs involved in synthetic drugs trafficking.
• Cocaine and heroin – aiming to: reduce cocaine and heroin trafficking to the EU and to disrupt the OCGs facilitating the distribution in the EU.
• Illicit firearms trafficking – aiming to: reduce the risk of firearms to the citizen including combating illicit trafficking in firearms.
• Organised property crime – aiming to: combat organised property crime committed by mobile OCG.
• Cybercrime – aiming to: combat cybercrimes committed by OCGs and generating large criminal profits such as online and payment card fraud, cybercrimes which cause serious harm to their victims such as Child Sexual Exploitation, and cyber-attacks which affect critical infrastructure and information systems in the EU.
5.14 It can be seen that the trafficking of cocaine and heroin are central themes of the EMPACT cycle. The EPDT project seeks to support the aims of the EMPACT cycle, Europol and the European Council through the analysis of ECRIS data and national criminal record data funded through the European Commission Justice programme.
acro.police.uk 11 6 Project aim and initiation
6.1 The EPDT Project was commissioned in January 2015. During this stage, three staff members were recruited into the specific roles for the project thereby establishing the project team. The project team consisted of a Project Manager, Project Support Officer and Intelligence Analyst.
6.2 The purpose of the project aimed to demonstrate how the analysis of criminal record information exchanged through ECRIS could be used as an intelligence tool to target the trafficking of illegal substances, specifically cocaine and heroin.
6.3 The project initially sought to identify key source countries within the EU by analysing criminal records to identify;
• persons convicted of production and distribution. • key countries for onward distribution through criminal records of those convicted of supplying the target drugs. • end user countries from the criminal records of people convicted of drug use and possession offences.
6.4 The development of these patterns over the life of the project were to be analysed to demonstrate where enforcement actions have impacted on these patterns and whether enforcement actions reduce the supply and useage, or displace the networks and trends. The project team also aimed to analyse the changes in drug use within MS for example, was there a move from cocaine and its derivatives to heroin or vice versa, or a move towards new synthetic drugs?
6.5 An advantage of using conviction data is that the research and intelligence is based upon actual confirmed offending rather than suspected offending. Conversely, a disadvantage in using conviction data carries inherent limitations. A number of court cases do not end in conviction, not because a drug has not been supplied or consumed, but because of a legal technicality, lack of evidence or other issues associated with due process, this does not mean the offence did not occur. Additionally, cases often change as they progress through the criminal justice system as various threshold tests are applied. This can result in charges being discontinued against some defendants and cases escalate up and down the level of severity i.e. an initial arrest for supply, becomes a conviction for possession. It should also be noted that both legislation and law enforcement activity and practice affects the numbers and types of offenders who enter the justice system and this varies between countries. For example, in some countries police may focus on supply activities and put less focus on arresting people who are drug
12 Criminal record analysis to support the European Pact on International Drug Trafficking users (or indeed the possession of drugs may not be a criminal offence), while in another country the police may actively target users more.
6.6 The target group for the provision of data extracted from criminal records are those departments which hold the relevant data, e.g. MS Central Authorities. The target groups for the benefits from the project are, again, the EU MS Central Authorities and the law enforcement community.
6.7 The project had three key objectives:
1. To evaluate how criminal records across the EU can be utilised to support an EU pact on international drug trafficking.
2. To identify a model that enables analysis of criminal records to continue once the project expires.
3. To identify how existing EU co-operation mechanisms can be enhanced by using criminal records to combat international drug trafficking.
6.8 In order to achieve these objectives the project was divided into three separate work streams;
Work stream one - Research and analysis to identify patterns of offending in international drug trafficking by utilising conviction data.
This work stream focussed on seeking to better understand how analysing bulk criminal record data from across the EU can assist in the fight against international drug trafficking.
The aim of the work stream was to conduct a large scale research project with 12 EU MS. MS were requested to disclose sanitised criminal record data to the project team in the UK which was analysed to identify trends and patterns in drug distribution.
Work stream two - Implement an IT capability to efficiently extract offence and conviction data from ACRO systems.
The premise was to develop and implement an IT capability to enable ACRO to search and extract data from the ECRIS system for intelligence purposes. This IT tool was required to extract not only drugs data relevant to this project but also any crime type for future use. The IT solution also needed the flexibility and portability to be transferred to other EU MS to allow them to conduct similar extractions and analysis.
acro.police.uk 13 Work stream three - Host an international closing event to relay the findings of the research to stakeholders.
This work stream aimed to maximise the value of the project and the IT tool. The conference on the 30th – 31st January 2017 aimed to enforce the business benefits realisation and make steps to ensure that through using the product, that the identification of drug trafficking across the EU will become easier.
6.9 The EPDT Project Initiation Document (PID) detailed a number of activities to be completed under each work stream. From this, the project team created a project plan with an aim to provide support to all agencies involved in the project through the two year study. The plan was;
• Review foreign national offending within the UK for the period 2011 – 2014 from the national criminal register (PNC), plot these convictions based on geography, nationality and drug type.
• Review reported convictions for 2011 - 2014 sent from and to the UK via ECRIS, plot these based on geography of offence and offender nationality.
• Engage with three co-beneficiary MS (Spain, Lithuania, and Romania) and seek to obtain the same level of data as above and plot in a similar manner.
• Seek assistance from a further eight MS to provide similar data. The selection of these MS were determined by the ability to provide data on;
• Offence location • Drug type • M.O. (Modus Operandi)
• Develop an IT solution that will enable required data to be extracted from the ECRIS database, flexible enough to be able to change crime type for varied analysis and encompass the ability to manipulate and present the data in a variety of ways.
14 Criminal record analysis to support the European Pact on International Drug Trafficking 7 Data sources
7.1 To retrieve the UK data for 2011 - 2014, the following data sources were used;
• European Information Management System (EIMS), the UK database that pre-dated ECRIS • ECRIS Notification In (NI) and Notification Out (NO) • PNC conviction data
7.2 In order to meet the project objectives, the project team initially aimed to analyse the EIMS data to cover the time period January 2011 to April 2012 and the ECRIS data from April 2012 to December 2014.
7.3 The data held within these two databases covers a multitude of different interactions between all MS. The project focussed on two specific elements of communication, firstly the information sent to a MS regarding the conviction of one their nationals within the UK, referred to as a NO. Secondly, the information received by the UK from a MS referring to the conviction of a UK national in their country referred to as a NI. In general, the convicting MS generates the NO and the MS of that person’s nationality receives the NI (see Appendix B which details this process using a flow chart).
7.4 The EPDT project team also utilised PNC data for the same four year period (2011 – 2014). This dataset provided a useful comparison basis for the ECRIS data to determine whether trends remained consistent across both datasets.
EIMS
7.5 Statistics were extracted from the EIMS database to cover the project date parameters January 2011 to April 2012 for both NO and NI.
7.6 Analysis of the EIMS data identified that drugs offences were categorised into one of the three following areas,
• ‘09h Other Drug Offences’ • ‘09a Drugs – Supply/Manufacture’ • Uncategorised offences
7.7 Due to a large proportion of uncategorised offences, combined with the difficulty in extracting the data from the EIMS system, it was recommended by the Analyst that the project team focus on analysing data from only the PNC and ECRIS systems.
acro.police.uk 15 ECRIS
7.8 ECRIS is based on a decentralised IT architecture whereby criminal record data is stored solely in national databases and exchanged electronically between the CA of EU MS through a standardised template. It uses reference tables listing common categories2 of offences and penalties. The table reflects the legal systems of 28 MS. It is a list of defined values that are common for all MS, this facilitates automatic translation and enhances mutual understanding of the information transmitted.
7.9 There are a number of obligations on MS relating to the information they are required to record and this generates a large number of individual ECRIS data fields, which the project team aimed to access, extract and analyse.
7.10 In developing a solution to meet the project objectives, the initial focus was the development of a process that focuses on the NO and NI transmissions. These transmissions are those generated by the following obligation;
7.11 The Council Framework Decision 2009/315/JHA impose the following obligations of the convicting MS:
• Each MS shall take the necessary measures to ensure that the nationality of an individual is recorded if she/he is a national of another MS,
• The convicting MS shall, as soon as possible, transmit any convictions as entered in their criminal register to the MS of that person’s nationality,
• If a person convicted in a MS is a national of several other MS, each shall be informed of the conviction(s),
• Subsequent alterations or deletions by the convicting MS shall be immediately transmitted to the MS of nationality.
7.12 To refine the data parameter further the project team reviewed all 1883 ECRIS common categories and focused only on the NO and NI connected to one of the five drug related categories as follows.
2 The common categories are umbrella offences that encapsulate similar offences under one of the 188 categories. They are not designed to set legal equivalencies between offences, penalties and measures existing at a national level. 3 The full table is available in Annex A of council Decision 2009/316/JHA
16 Criminal record analysis to support the European Pact on International Drug Trafficking ECRIS category code Common category title
O-00-070000 Offences related to drugs or precursors, and other offences against public health
Offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors O-00-070100 not exclusively for own personal consumption
Illicit consumption of drugs and their acquisition, possession, manufacture or production O-00-070200 exclusively for own personal consumption
O-00-070300 Aiding or inciting others to use narcotic drugs or psychotropic substances illicitly
O-00-070400 Manufacture or production of narcotic drugs not exclusively for personal consumption
7.13 The following ‘obligatory’ information must always be transmitted, unless, in individual cases such information is not known to the central authority of the convicting MS.4
Obligatory information Optional information
Information of the convicted person:
Full name, date of birth, place of birth (town and State), The national identity number, full name of the convicted gender, nationality (can be multiple), ID document number person’s mother and/or father, residential address, alias including type of document and category, if applicable, details, electronic fingerprints, any additional valuable previous name(s) remarks related to the person
Information on the nature of the conviction:
Country of the conviction, date of conviction, name and End date of the retention period for this conviction, the reference of the competent authority, decision date and code of the competent authority, any additional valuable date on which the decision became final and legally remarks related to the person applicable.
Information on the offence giving rise to the conviction:
Common category, national title, applicable legal Information on the offence giving rise to the conviction: provisions, information regarding recidivism, responsibility national code, start and end date of offence, offence exemption, continuous offence location, number of occurrences, level of participation, any additional valuable remarks related to the person
Information on the sanction:
Information on the contents of the conviction: type of Information on the contents of the conviction: national sanction, sanction common category, sanction national code, an indication of whether the sanction represents title, information on whether the sanction is linked to an alternative to another sanction, sentenced start and being a minor end date, sentence duration, start and end date for the execution of the sentence, number and value of fines to be paid and in which currency, suspension terms, any additional valuable remarks related to the person.
4 ECRIS–BA–Business Analysis–20140704–EN–V.19
acro.police.uk 17 Police National Computer
7.14 The Police National Computer (PNC) is the name given to the UK national criminal register. As an additional data source the project team sought PNC data for the four year period (2011 – 2014) which allowed for direct comparisons to be made between both ECRIS and PNC for the years 2013 and 2014.
7.15 There are in excess of 23,000 individual offences on the PNC with over 1,000 individual offences relating to drugs and drugs trafficking offences.
7.16 A meeting with PNC Services allowed the team to better understand the PNC data extraction process. The extraction process was subject to several limitations.
• Data was unable to be extracted using date parameters, therefore data received will be from when PNC first commenced in 1977 to present day.
• Each PNC data request is limited to only 20 offence codes; to overcome this the Project Analyst grouped individual offences under ‘umbrella’ offence codes. For example, a request for offence code 29.1 returned all offences within offence code 29.1 (e.g. 29.1.60, 29.1.61 and 29.1.62) as a result, this reduced the number of offence codes at the time of request making the process more manageable.
7.17 To retrieve the relevant offence codes the analyst collated all drug related offences linked to the five common categories and customs offence category from the ‘National Offences’ spreadsheet.5 This amounted to over 2000 offences. Approximately 50% of the offences were removed as these offences were deemed not relevant to the project (e.g. medicinal offences).
7.18 The remaining 1000 offence codes were then grouped together into 21 ‘umbrella’ codes which encompassed multiple offences. For example, the ‘umbrella’ code 29.1 incorporated 112 individual offences.
7.19 A PNC QUEST (Query Using Extended Search Techniques) search was conducted at ACRO on each of the 21 codes to identify the number of PNC records that contained an offence under the ‘umbrella’ code. This process assisted in identifying which of the 21 codes would form the first request to PNC Services (Appendix C).
7.20 The QUEST search revealed that offence code 9.1 returned approximately 1.6 million items. Analysis identified a large portion of data within 9.1 related to cannabis which was not going be used as the project focus was on cocaine and heroin. Offence code 9.1 was removed from this first request and the 20 remaining ‘umbrella’ offence codes were submitted to PNC Services as the projects’ first data request.
5 National Offences_UK_uk V10 GSA
18 Criminal record analysis to support the European Pact on International Drug Trafficking 7.21 The second data request required further work to identify those offences within offence code 9.1 relating to cocaine or heroin. In total, 43 offences under 9.1 related to either cocaine or heroin. A QUEST search identified the volumetric data linked to each offence code under 9.1 (Appendix D). The 20 offence codes with the highest volumetric data linked to 9.1 were then submitted as the second request to PNC services.
7.22 The project team were able to make two separate requests to PNC Services against 40 ‘umbrella’ codes that searched on over 1,000 individual drug offences. The first request aimed to capture a wide range of drugs data relating to all classes of drugs, whereas the second request was focussed primarily on cocaine and heroin.
7.23 The project team received over 60 million rows of data from PNC Services. The first PNC request yielded a broad range of data on all classes of drugs. As the project focus was on cocaine (including crack) and heroin the project team opted to utilise the data from only the second PNC request as it was not possible to identify which of the Class A offences related to cocaine (including crack) or heroin.
7.24 The dataset was ‘cleaned’ by removing erroneous data to identify those convictions that occurred between 2011 and 2014 relating to cocaine, crack cocaine and heroin. This process reduced the data from 60 million to 111,576 offences which related to UK and Foreign National Offenders (FNO).
7.25 An in depth process of how the PNC data was ‘cleaned’ and how the ‘nominal’, ‘offence’ and ‘offence address’ PNC files were merged is recorded in a separate document, named ‘PNC Acquisition’. This is available on request.
acro.police.uk 19 8 Member state engagement
8.1 The initial project bid recommended that the project would aim to retrieve the necessary data from 12 MS within the time frame of the project.
8.2 At the commencement of the project all 28 MS were contacted seeking their assistance and support. The structure of how the project engaged with MS was based on a five stage approach as follows;
a) Direct contact with the ECRIS manager introducing the aims and objectives of the project.
b) Having identified the appropriate contact, a questionnaire (Appendix E) regarding national criminal records database structure was dispatched (8.5).
c) On the receipt of the questionnaire responses, a request was sent for ECRIS volumetric data to identify the proportion of drug offences against the five drug common categories. This was known as phase one (8.8).
d) On receipt of volumetric data, a further request was made to provide detailed sanitised information in relation to the results of the phase one data. This was known as phase two.
e) Further engagement with individual MS was required, seeking data from national criminal record databases and/or providing funding to support extract of data above.
8.3 In addition to the three partner countries, the project aimed to invite a further eight MS to share data. The following methods were used to identify those MS believed to add value to the project:
• The questionnaire ascertained information relating to each EU MS criminal record database, for example it identified those countries that recorded key information such as, offence location, type of drug (cocaine, heroin), or an M.O.
• All project board members were requested to make considerations and provide a proposal for the MS they believed may be the best ones to engage with for example, the project team asked the board to consider the MS strategic positioning and the IT capability of each MS.
• The project team visited Europol to present the aims and objectives of the project to the 28 International Bureau liaison officers covering all MS. Twenty two International Bureau liaison officers attended the presentation. The liaison officers were encouraged to engage with their ECRIS Single Point Of Contact (SPOC) in order to expedite the return of the questionnaire and phase one data.
All of these methods assisted the project team in identifying those MS that were willing to engage with the project.
20 Criminal record analysis to support the European Pact on International Drug Trafficking Questionnaire
8.4 The first step was to identify what data each MS held, the custodian of the data and whether they would be prepared to share or exchange it for the benefit of the project. As each MS is required to transmit details of criminal convictions across the EU utilising ECRIS it was envisaged that the acquisition of data statistics would be relatively straight forward.
8.5 The project team sent a questionnaire to each MS requesting responses to ten questions (Appendix E). The questions were focussed on the structure of the MS criminal record database, whether any analysis was conducted on this, data structure and their views on further involvement within the project.
8.6 All 28 MS responded to the questionnaire. The responses took between four and thirteen months to arrive. Whilst all MS could provide answers to the questionnaire, not all were prepared to engage any further.6
8.7 Reasons that MS cited for not participating in the project varied from not having enough resource to commit to the project to not having the relevant data to share.
Phase one
8.8 Most EU MS are connected and exchanging criminal record data through ECRIS (see Appendix A for connectivity matrix). The team worked closely with the EU Commission in order to identify the ECRIS volumetric data for all EU MS for 2013 and 2014 in respect of NO and NI. This volumetric data identified the number of transmissions made by an individual MS to every other MS since they joined ECRIS.
8.9 The European Commission couldn’t however identify what the volumetric data specifically related to in terms of individual ECRIS crime categories. As a result, the volumetric data provided by the European Commission could have related to any one of the 188 common categories. Therefore data held by the European Commission could not assist the project.
8.10 As a result the project team requested each MS to provide volumetric data for both NO and NI interactions relating to the five ECRIS common categories for drugs trafficking. Sixteen MS were able to provide the project with volumetric data relating to the five ECRIS common categories, also known as phase one data. It provided the project team with very basic data but it identified the volume of data owned by each MS and also gave an indication of the likely participation of the MS in the overall project.
6 Denmark, Bulgaria, Luxembourg, Portugal, Slovak Republic, Sweden were not able to engage any further with the project once the questionnaire had been completed acro.police.uk 21 Phase two
8.11 The next phase was to seek the provision of detailed but anonymised data relating to drug convictions linked to the five ECRIS common categories. This was referred to as phase two. A total of nine MS responded including Germany, Belgium, Italy, Croatia, Hungary and the four partner MS; Spain, Lithuania, Romania and the UK.
8.12 The results of the engagement demonstrated the difficulties surrounding the project aims. Although it was initially agreed in the project bid that the project team would aim to engage and retrieve data from 12 MS within the timeframe of the project. This was not achieved due partly to the protracted lengths of time it took to get agreement from specific MS and the limitations surrounding individual MS data and extraction capabilities (Appendix F).
22 Criminal record analysis to support the European Pact on International Drug Trafficking 9 Data acquisition, extraction and quality assurance
ECRIS
9.1 Each EU MS supporting the EPDT project was requested to provide data in an Excel format with anonymised individual data contained in separate rows. The data parameters ranged from 1st January 2011 to 31st December 2014. The project team recognised that ECRIS data would only be available from the point the MS went live with ECRIS. For this reason the project team requested access to the national criminal record data from 2011 to 2014. To minimise the data manipulation, the project team requested the data in a specified format for NI (Appendix G) and NO (Appendix H).
9.2 The project team devised a quality assurance framework by checking the data returned from each MS against the UK ECRIS data. This ensured that the data and information being provided to the project team was accurate.
9.3 On receipt of EU MS data, the Project Analyst verified the NO data submitted by each EU MS by comparing it against the number of NI received by UKCA-ECR from that relevant MS. The same process also applied to the NI data by comparing it against the number of NO.
9.4 The quality assurance framework was used on all ECRIS datasets received from the nine participating MS. These measures identified initial differences between the data supplied and the dataset used to verify the information. Where there were inconsistencies the individual MS was notified. These validation queries were reviewed by the participating countries and changes were made to the dataset where necessary. The revised dataset was subject to the same quality assurance methodology. Only once the accuracy of the data was verified did the project team proceed to the next analytical stage.
9.5 To ensure consistency across all MS submitting data to the EPDT Project, the project team designed a process map and data template which documented the process steps of how to extract and format the data from ECRIS. This process map advised all data providers to supply the data using ‘final decision date’ and not ‘message sent/received’ search fields. Both the process map and template allowed for consistency by ensuring all countries were reporting their data consistently to avoid misinterpretation of data.
acro.police.uk 23 PNC
9.6 On receipt of the PNC data, several quality assurance methods were implemented to help identify any discrepancies in the data.
9.7 Data reconciliation formed part of this quality assurance process to ensure the project team had received all the expected data. This process identified that the project team did not receive a complete dataset and there were data files missing. As a result the PNC files received were archived and the PNC enquiry was re-run and the files were resent to the project team. On receipt of the new PNC data the project team reconciled the PNC files to ensure the team had received the complete dataset.
9.8 The ECRIS NO dataset was used as a comparator to evaluate the accuracy of the PNC data. PNC data (1,114 offences) were validated against the NO offences which identified 98.38% accuracy. Further analysis relating to the 1.62% difference identified that these offences had been subsequently altered on PNC but not yet transmitted to the relevant MS via ECRIS.
9.9 By implementing the quality assurance methods it ensured accuracy of both ECRIS and PNC datasets allowing the project team to progress to the analytical phase with confidence that the data collected from ECRIS and PNC was fit for purpose, relevant and complete.
MS national data
9.10 The MS national criminal register data was subject to the same quality assurance methodology as the ECRIS data by verifying the national data supplied by each MS against the NI data received from that relevant country.
24 Criminal record analysis to support the European Pact on International Drug Trafficking 10 Data research and analysis
10.1 What became evident from the analysis of the phase one and phase two data was the incompatibility of data based on a variety of issues, not least the contrast in MS legislation. National drug laws in MS identify significant variations in the manner to which convictions are categorised and recorded across EU MS.
10.2 In the UK there are over a thousand different drug offences that cover a multitude of specific drug types. Offences relate to the possession, supply, distribution of a particular drug or it is classified into Class A, B or C. As both cocaine and heroin fall within Class A together with a number of other illicit drugs such as LSD and MDMA it is impossible to identifiy all of the cocaine or heroin based offences.
10.3 Neither Scotland nor Northern Ireland have specific offences relating to cocaine or heroin relying on the class of the drug for categorisation. This occurs across most of the EU MS who equally do not necessarily differentiate between the different drug types nor do they differentiate between cultivation, possession and supply type offences. To successfully identify the level of conviction for a specific drug type on a comparable level is therefore extremely difficult.
10.4 Offence location is not typically recorded at the crime reporting stage and some MS are therefore unable to extract this data for the project. The project team used the court location for both Spain and German datasets as offence location was not available. This raised the question on whether people are likely to be convicted in the region they were arrested. This has been cited in the data limitations and country analysis sections of this report.
10.5 The project team also identified differences in ECRIS retention periods throughout Europe. For example, Germany only retains the NO data for one year after this it is deleted, whereas currently, Spain do not delete ECRIS notifications or requests.
10.6 There is another international project that may assist the EU in the area of criminal records which is being supported by the EMCDDA. This relates to standardising the reporting protocols across the EU.
10.7 The issue in the variance of crime classification and crime recording across the world is an on-going issue. The EMCDDA has been collecting drug law offence data for over 15 years with similar challenges to those experienced by the EPDT project. Their latest European Drugs report7 commences with the following;
“Reports of offences against national drug legislation (use, possession, trafficking, etc.) reflect differences in law but also the different ways in which the law is enforced and applied, and the priorities and resources allocated to specific problems by criminal justice agencies. In addition, information systems
7 http://www.emcdda.europa.eu/stats09/dlo/methods
acro.police.uk 25 on drug law offences/offenders vary considerably between countries, especially as regards recording procedures, definitions and statistical units (see below).
“The term ‘reports for drug law offences’ covers different concepts, varying between countries. Drug law offences usually refer to offences such as drug production, trafficking and dealing as well as drug use and possession for use. Although in some countries, drug use and/or possession for use are not considered as criminal offences and attract administrative sanctions, reports for these were included in the data presented here.
“The stage within the criminal justice system at which data have been reported and recorded, vary sometimes across countries. For example, data on drug law offences might be recorded at an initial stage when a first report is made by law enforcement agencies, or after investigation by the Judicial Police, or even following a decision for a charge to be issued by the Prosecutor.
“Statistical units vary between countries. Some countries record offences while others record persons (or presumed offenders). Among those recording offences, some record all offences reported to them, while others record only the main offences — i.e. in the case of several offences committed by the same person, only the most serious offence (usually the one that attracts the highest penalty) is recorded. Among countries recording persons, some record a number of individuals being reported during the year, while others report only a number of different individuals reported during the year. In the former case, an individual reported twice during the same year will be counted twice while in the latter case he would be only counted once in the statistics. In addition to these, when considering breakdowns by drug, here too, some countries report all drugs mentioned in a case while others record only the main drug (defined according to different criteria in different European countries).
“These differences — mainly in the stage at which the statistics are made and in the type of statistical units — lead to major difficulties when comparing data from different European countries.”
10.8 What the EMCDDA have established is the need to develop a set of crime and supply indicators which has also been recognised as a priority across the EU. This revision also takes account of the introduction of world-wide definitions of criminal offences for monitoring purposes, namely the International Classification of Crime for Statistical purposes.
10.9 In the wider context of the EU, a closer working relationship with, or the developed analysis of EMCDDA data which incorporates ECRIS criminal conviction data may provide a more refined benefit to the EU pact over the forthcoming years.
26 Criminal record analysis to support the European Pact on International Drug Trafficking 11 The IT solution
11.1 The focus of work stream two was to identify a solution suitable for the extraction of data across all areas of criminality within ECRIS. Each MS has their own national interface with ECRIS and the IT solution should meet the requirements of all MS.
11.2 The challenge of identifying a suitable IT solution was difficult for a number of reasons.
• The IT solution was required to support the internal end users of ECRIS across all 28 MS with the ability to extract and manipulate any data that is contained within ECRIS for analytical purposes.
• The tool should be cost effective and easily accessible to enable EU colleagues to purchase the tool for analysis of data once the project has reached its two year completion.
11.3 The initial view was to identify an existing accepted data analysis tool such as Microsoft ‘BusinessObjects’. In brief, this process had a number of significant drawbacks, mainly cost based on the need to construct ‘universes’ and ongoing licence purchase renewals. Secondly, this system would only work against one national interface and not have the portability to work across a multitude of ECRIS databases.
11.4 The focus therefore shifted to try and identify a solution that worked across a variety of ECRIS software applications, enabling analysis and delivery of results as well as being cost efficient to enable purchase by other MS. Research showed there are a large number of commercially available software packages providing business intelligence capabilities including Microsoft Power BI.
11.5 The business requirement needed to identify a starting point for separating the myriad of software applications. Having reviewed the system architecture for each MS in respect of ECRIS it became apparent that a common denominator was the Microsoft operating system. For this reason, the project team opted for a solution designed to work with Microsoft, a system called Microsoft Power BI.
11.6 The progress of testing Power BI was hindered by the need to introduce an upgraded IT system in the host organisation and initially prevented on-site development and testing of this product. The short term solution was to test Power BI on a standalone system using test data. This led to the creation of a demonstration model using data from Spain and Lithuania which was presented to those two MS.
11.7 Power BI simplifies data discovery, access and collaboration and is available at little or no cost as the majority of EU MS have some form of Microsoft system built into their IT framework. The full IT specification is listed in Appendix I.
acro.police.uk 27 There are four components to Power BI:
• Power Query – this component allows you to connect to a variety of different data sources such as ECRIS, extract data from the source quickly and easily and provide steps to ‘clean’ the data before it gets loaded into Excel.
• Power Pivot – whereas, traditional PivotTables are limited to just one source table, Power Pivot allows the end user to create relationships between multiple data sources. This component also provides the capability to work with very large data volumes by using the Excel data model.
• Power View – provides more options for the end user to visualize the data by creating attractive, interactive dashboards and enables the end user to geographically map the data (if location details are available).
• Power Map – allows the end user to plot geographic data. Once this data is mapped, the end user has the capability to pan, zoom and display data over many locations. The end user can then analyse that data in 3D and create cinematic tours to share with others.
11.8 The Power BI solution enabled the end user to efficiently extract data from ECRIS allowing for the project team to progress with the data analysis. Beyond the life of the project ACRO will have the ongoing ability to search and extract data using this tool. This will support ongoing work by utilising ECRIS criminal record data where possible.
11.9 The Power BI solution was used by the project team to analyse the data gathered throughout the project and to support the findings at the end of the project conference. This was impactive and extremely well received.
28 Criminal record analysis to support the European Pact on International Drug Trafficking 12 Serious and Organised Crime
12.1 Various definitions exist to describe what constitutes ‘organised crime’. The National Crime Agency (NCA) define organised crime as “serious crime planned, coordinated and conducted by people working together on a continuing basis. Their motivation is often, but not always, financial gain. Organised criminals working together for a particular criminal activity or activities are called an Organised Crime Group (OCG).” 8
12.2 OCGs are a threat to society across the EU and worldwide. There is a global concern regarding the negative impacts that organised crime has on individual citizens, communities and businesses.
12.3 OCGs are active globally. It is believed that there are 6,000 active OCG in the UK alone9 consisting of nearly 50,000 individuals.
12.4 Drug markets continue to be one of the most profitable areas for OCGs. The impacts that drug markets have on society are correspondingly large and go beyond the harms caused by personal drugs use. It causes significant harm to the social; and economic well-being of a country as a whole, as well as affecting a country’s reputation both nationally and internationally.
12.5 EMCDDA and Europol estimated in the EU drugs market report that the retail drug market was worth at least €24 billion (range €21 to €31 billion) in 2013, with the cannabis market being the largest, making up about 38% of the total, followed by heroin (28%) and cocaine (24%).10
12.6 OCG exploit the Shengen Agreement that enables the free movement of people for lawful purposes within the Schengen Area. The Schengen area provides a comfortable operating area for trafficking drugs and it will continue to be exploited by OCG networks as the free movement across Europe’s internal borders reduces the risk of detection and identification.
12.7 The production and trafficking of drugs are activities perpetrated by OCG networks operating across geographical boundaries and therefore a transnational and multi-agency response is required to effectively prevent and counter organised crime. In 2010, the EU Council dedicated an EU pact to combat international drugs trafficking, focussing specifically on cocaine and heroin. The pact noted that organised crime networks are international in scope which requires a European-level response and it recognised that EU MS are affected by trafficking in different ways.
8 http://www.nationalcrimeagency.gov.uk/crime-threats/organised-crime-groups 9 http://www.nationalcrimeagency.gov.uk/publications/668-intelligence-assessment-pathways-into-serious-and-organised-crime-final/file 10 European Monitoring Centre for Drugs and Drug Addiction and Europol (2016), EU Drug Markets Report: In-Depth Analysis, EMCDDA–Europol Joint publications, Publications Office of the European Union, Luxembourg.
acro.police.uk 29 13 Research
13.1 Drugs trafficking continues to be a matter of concern for all EU MS, both in respect to public order and public health. In response to this, the EMCDDA and Europol issued their first EU drugs market report in 2013 providing an overview of the EU drugs market in its entirety. In their latest report from 2016, the EMCDDA and Europol map the routes from countries of production, through countries that act as transhipment and entry points to the European market, together with the end user markets in Europe, including the UK.
13.2 EMCDDA identifies cocaine as the most commonly used Class A stimulant in Europe and the second most seized drug in Europe, after cannabis.11 The retail market is estimated to be worth at least 5.7 billion Euros per year12 and it is reported within Europe, the greatest numbers of consumers are in the UK, followed by Spain, Italy, Germany and France.13
13.3 Analysis of cocaine and heroin seizure data reported by EMCDDA (figure 13.1) confirmed cocaine was by far the most commonly seized Class A drug across Europe. Approximately 48,489kg of cocaine was seized in Europe and Turkey in 2014, over twice as much as heroin, of which 20,087kg was reportedly seized. Figure 13.1 EMCDDA seizure data (2011 - 2014)14 & 15
Heroin (kg) Cocaine (kg) Country 2014 2013 2012 2011 2014 2013 2012 2011 Austria 56.16 80.25 222.10 64.87 30.98 24.74 64.64 138.93 Belgium 149 1182.37 112.49 140.35 9293 6486.23 19177.99 7999.21 Bulgaria 940.49 156.86 285.32 385.46 26.87 19.54 115.20 4.00 Croatia 46.85 10.43 29.74 33.1 5.84 9.1 5.63 4.07 Cyprus 0.005 0.74 1.13 0.60 31.75 3.31 7.01 3.38 Czech Republic 156.81 5.05 7.6 4.7 5.4 35.79 8.05 16 Denmark 13 14 41 37 90 681 42 43 Estonia 0.00 0.00 0.05 2.78 3.37 0.83 Finaland 0.09 0.20 0.07 1 6.3 4.5 25.7 3.5 France 990 570 701 883 6876 5612 5602 10834 Germany 779.95 270 242 498 1567.91 1315 1258 1941 Greece 2527.66 235.11 331.10 360.59 297.22 706.08 200.7 463.09 Hungary 70.06 5.72 2.52 3.17 39.65 8.13 13.31 12.55 Ireland 61 60 32 66 459 179 Italy 931.13 881.85 940.25 813.49 3865.80 4966.14 5300.26 6344.04 Latvia 0.77 0.719 1.39 0.44 7.86 0.575 1.07 81.49 Lithuania 6.88 13.20 0.50 10.60 116.1 3.3 120.1 9.8 Luxembourg 6.73 3.81 2.65 23.90 4.695 0.847 2.013 24.435 Malta 1.77 1.30 1.33 3.97 5.27 3.6134 142.86 5.35 Netherlands 750 400 10000 10000 Norway 44.40 55.10 44.50 13.30 149 187.7 47.5 46.2 Poland 272.71 48.68 35.62 51.36 31.46 20.57 213.39 78.12
11 http://www.emcdda.europa.eu/system/files/attachments/2641/Cocaine%20trafficking_POD2016.pdf 12 European Monitoring Centre for Drugs and Drug Addiction and Europol (2016), EU Drug Markets Report: In-Depth Analysis, EMCDDA–Europol Joint publications, Publications Office of the European Union, Luxembourg 13 UNODC World Drugs Report (2010). 14 http://www.emcdda.europa.eu/modules/sbdata/SBDataService2016.cfc?method=fetchxlsx&tableid=SZR-10-0 15 http://www.emcdda.europa.eu/modules/sbdata/SBDataService2016.cfc?method=fetchxlsx&tableid=SZR-8-0
30 Criminal record analysis to support the European Pact on International Drug Trafficking Heroin (kg) Cocaine (kg)
Country 2014 2013 2012 2011 2014 2013 2012 2011 Portugal 38.69 55.46 65.54 72.91 3715.15 2439.72 4019.87 3678.22 Romania 25.79 111.56 45.217 12.91 34 53.34 54.70 161.04 Slovakia 0.05 0.19 0.26 0.32 0.02 1.46 1.75 35.27 Slovenia 4.87 7.65 20.34 4.39 181.99 3.314 26.82 1.697 Spain 244.44 291 282 412 21682 26701 20754 16609 Sweden 23.5 6.13 6.8 21.4 29 81.06 34.4 88.7 Turkey 12755.54 13480.06 13300.68 7293.99 393.20 449.90 475.86 591.90 UK 784.9 831 1968 3561.5 3325 3568 Total 20087.35 18333.34 18364.15 13546.87 48489.25 53445.46 71502.19 62965.82
13.4 In 2011, Belgium, France, Italy, The Netherlands and Spain reportedly seized the largest quantities of cocaine in Europe, accounting for approximately 82% of the total cocaine seized throughout Europe. In 2014, the same countries, with exception of The Netherlands (no data), reported the highest cocaine seizures accounting for approximately 86.74% of all European seizures.
13.5 It is widely recognised that cocaine is trafficked into the European market from the countries of production in South America, particularly Colombia, Peru and Bolivia.16 Current knowledge on drugs trafficking recognises that that there are two main cocaine trafficking routes before entering Europe.
“The first is the Caribbean, where the Dominican Republic and Jamaica are considered the main hubs, although operations elsewhere appear to have pushed some trafficking through the eastern Caribbean”.
The second trafficking route transits the “West African mainland and neighbouring islands, Cape Verde, Madeira, and the Canary Islands”.17
13.6 The most important entry points for cocaine destined for Europe is either via Spain or Portugal where it crosses the Atlantic and enters Western Europe, or via the ports in the Netherlands and Belgium in Northern Europe.18
13.7 In 2011, the EU countries reporting the highest heroin seizures were the UK, France, Italy, Germany and Spain, accounting for approximately three quarters of the heroin seized in the EU. Whereas in 2014, analysis identified a shift in the ‘top five’ countries to Greece, France, Bulgaria, Italy and the UK. Both Greece and Bulgaria reported significantly larger seizures in 2014 than in 2011, with increases of 723.45% and 144.16% respectively. Current knowledge on drugs trafficking recognises that Greece and Bulgaria have a key role in trafficking heroin to Europe; both key transit points on the ‘Balkan route’ linking Afghanistan, Iran and Turkey to Europe.
16 http://www.emcdda.europa.eu/system/files/attachments/2641/Cocaine%20trafficking_POD2016.pdf 17 http://www.emcdda.europa.eu/topics/pods/cocaine-trafficking-to-europe#panel1 (rounded to 2 decimal points) 18 http://www.emcdda.europa.eu/topics/pods/cocaine-trafficking-to-europe#footnotes
acro.police.uk 31 13.8 EMCDDA19 reports that heroin enters South Eastern Europe via the well-established Balkan route from Afghanistan to reach the “high-value” western European markets. From Afghanistan, there are three main routes before it enters Europe;
• The ‘northern branch’ – crosses Bulgaria and Romania to Hungary, Austria, the Czech republic, Poland or Germany generally by land. • The ‘southern branch’ – traverses Greece, Albania and Italy, mostly by sea.
• The ‘central branch’ – runs through Bulgaria, the former Republic of Macedonia, Serbia, Montenegro, Bosnia and Herzegovina, Croatia and Slovenia, and into Italy or Austria, essentially by land.20
19 https://www.unodc.org/documents/data-and-analysis/Studies/Illicit_DT_through_SEE_REPORT_2014_web.pd 20 http://www.emcdda.europa.eu/publications/eu-drug-markets/2016/online/heroin/trafficking-supply
32 Criminal record analysis to support the European Pact on International Drug Trafficking 14 United Kingdom
14.1 The project team sourced the following data:
Data Source Type Date Parameters
ECRIS NO 27/04/2012 - 2014
ECRIS NI 27/04/2012 - 2014
PNC 2011 - 2014
14.2 Data for the UK analysis was obtained from PNC and ECRIS (NO and NI data). PNC was used as the primary data source for the following reasons;
• PNC contains a wider range of data (covering the full project date range from 2011 – 2014) than ECRIS which was implemented in the UK on the 27th April 2012.
• The potential volume of data from PNC is substantially larger than ECRIS as the availability of ECRIS data is limited to only European notifications.
• PNC permits more detailed examination of offending patterns as:
o The project team were able to geographically plot location data using Police Force Station (FS) codes. An FS code reveals the address of the nearest operational police station the subject was taken to at the point of arrest. Geographical analysis was not possible using the ECRIS data as offence location is not typically transmitted between MS.
o The project team were able to analyse the threat posed by EU and Non EU nationals in order to inform a full picture of the risk that foreign nationals pose in England and Wales.
14.3 The project team were unable to retrieve the sanction data for both ECRIS and PNC datasets and therefore discounted the sanction data from any UK analysis.
14.4 The UK analysis is based on data for England and Wales. This is because neither Police Scotland nor the Police Service of Northern Ireland (PSNI) specify cocaine, crack cocaine or heroin in their legislation, albeit Scotland do record some drug types, such as MDMA. The default position for both forces appears to be that offences are recorded as possession/supply etc. of a ‘Class A’ drug rather than specifying the type of drug. The project team sought assistance from Police Scotland and PSNI to identify those offences relating to either cocaine (including crack) or heroin but were unable to further this enquiry and for this reason the analysis reports only on data from England and Wales.
acro.police.uk 33 14.5 The England and Wales analysis is limited to those offences with cocaine, crack cocaine or heroin in the national title (unique title of the offence known at a national level). It does not include those offences recorded as ‘Class A’ due to the same reasons given for Scotland and PSNI. Therefore, offences related to any other drugs do not form part of the UK analysis.
14.6 The project team were unable to geocode precisely the offence address as the PNC data only provided approximately 35% of the offence addresses committed by FNO. As a result, the project team opted to use the nearest police station by referring to the force station (FS) codes. This allowed the project team to analyse the data per police force area and also enabled the project team to geographically plot over 99% of the drugs offences committed by FNO.
14.7 Various methods are used to traffic drugs into the UK, which is reported to be one of Europe’s largest and profitable markets. Therefore, the UK remains an attractive country for OCG as street level prices are reported to be some of the highest in Europe. The geographical positioning of the UK in the EU also makes it an ideal country for the onward transmission of drugs to other countries.
14.8 Most of the drugs entering the UK follow well-established trafficking routes. Cocaine is trafficked into the UK from the countries of production in South America, primarily Colombia with the Caribbean, mainly Jamaica acting as a major transhipment point for cocaine, produced in South America before entering the UK. Whereas, the primary heroin trafficking route is overland from Afghanistan to the UK, transiting Iran and Pakistan.
14.9 The EMCDDA seizure statistics for the UK identify that cocaine is the main illicit class A drug seized. Cocaine seizures remained steady from 2011 (3,568kg) through to 2013 (3,561.5kg). Whereas, heroin seizures have declined year on year from 2011 (1,968kg) to 2014 (784.9kg).
14.10 In England and Wales, there were a total of 111,575 drug convictions recorded on PNC for UK and FNO offenders between 2011 and 2014. The number of offences decreased year on year from 2011 (30,530) to 2014 (26,568). This decrease is largely driven by the reduction in possession of drugs, from 18,836 offences reported in 2011 to 15,177 in 2014, a decrease of 19.43%, whereas supply type offences remained relatively stable. The decrease could be attributed to one or more reasons including reduced availability, the effects of law enforcement activity, or competition with other drugs, such as new psychoactive substances (NPS).
14.11 Analysis of the nationality of offenders within the UK highlighted the international diversity of drug offenders. From 2011 to 2014, over 190 different nationalities were convicted in England and Wales for drug offences. UK nationals accounted for 89.65% of the total offence count, compared with 3.51% relating to EU FNO and 6.51% for Non EU FNO and the remaining 0.33% unknown (figure 14.1).
34 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 14.1 PNC offence data for England and Wales (2011-2014)
Total UK EU FNO Non EU FNO Unknown
Offences 111,575 100,026 3,917 7,268 364
Offenders 75,185 67,877 2,942 4,028 338
14.12 Unless stated otherwise, all UK nationals have been excluded from all subsequent UK analyses. After removing UK nationals, 11,549 offences remained which related to 7,308 offenders.
14.13 Figure 14.2 displays the top ten FNO nationalities to be convicted for drug offences. The top ten nationalities account for 51.70% of the total foreign offence count. The remaining 48.30% is made up of 185 different nationalities.
Figure 14.2 - Top ten Non-UK nationals convicted of drugs offences in England and Wales (2011-2014)
Nationality Number Percentage
Jamaica 1,580 13.68%
Somalia 803 6.95%
Poland 546 4.73%
Pakistan 509 4.41%
Portugal 503 4.38%
Republic of Ireland (R.O.I) 503 4.36%
Lithuania 409 3.54%
India 382 3.31%
Albania 368 3.19%
Unknown 365 3.16%
14.14 Four of the Non UK nationalities (Poland, India, R.O.I and Pakistan) in figure 14.2 feature in the top five of the Non-British population in England and Wales by nationality21 (figure 14.4), suggesting a possible correlation between the size of foreign communities in England and Wales and the volume of offending that may be attributable to them.
21 Annual Population Survey (APS), ONS
acro.police.uk 35 Figure 14.3 - Distribution of the top five foreign national population in England and Wales for 2013 and 201422
England 2013 Poland 605,000 India 320,000 R.O.I 279,000 Pakistan 181,000 France 146,000
England 2014 Poland 724,000 India 338,000 R.O.I 276,000 Wales 2013 Pakistan 201,000 Poland 22,000 Romania 167,000 R.O.I 9,000 India 5,000 Malaysia 4,000 Romania 3,000 Wales 2014 Poland 24,000 R.O.I 10,000 India 6,000 Hungary 4,000 Eritrea 4,000
22 Annual Population Survey (APS) - Office for National Statistics
36 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 14.4 - Distribution of the top five foreign national population in England and Wales for 2013 and 201423
North West 2013 North East 2013 Yorkshire & Poland 62,000 Poland 10,000 The Humber 2013 Pakistan 32,000 India 6,000 Poland 58,000 R.O.I 32,000 China 5,000 Pakistan 24,000 India 25,000 R.O.I 5,000 India 16,000 Nigeria 12,000 Pakistan 3,000 Lithuania 13,000 R.O.I 12,000 North West 2014 North East 2014 Poland 75,000 Poland 13,000 Yorkshire & R.O.I 35,000 India 6,000 The Humber 2014 Pakistan 34,000 Pakistan 5,000 Poland 60,000 India 28,000 China 5,000 Pakistan 26,000 China 12,000 R.O.I 3,000 India 15,000 R.O.I 14,000 Latvia 13,000
West Midlands 2013 East Poland 59,000 Midlands 2013 India 36,000 Poland 62,000 Pakistan 29,000 India 27,000 R.O.I 25,000 Latvia 16,000 Romania 15,000 Lithuania 12,000 West R.O.I 9,000 Midlands 2014 East Poland 80,000 Midlands 2014 India 46,000 Poland 79,000 Pakistan 30,000 India 25,000 R.O.I 22,000 R.O.I 16,000 Romania 14,000 Lithuania 14,000 Latvia 13,000
South West 2013 Poland 51,000 R.O.I 17,000 India 16,000 East 2013 Philippines 9,000 Poland 74,000 Germany 9,000 R.O.I 34,000 South West 2014 Lithuania 31,000 Poland 60,000 USA 27,000 India 20,000 India 23,000 R.O.I 17,000 East 2014 Portugal 12,000 Poland 78,000 Spain 12,000 R.O.I 31,000 USA 28,000 London 2013 Portugal 27,000 South East 2013 Poland 143,000 Lithuania 22,000 Poland 87,000 India 131,000 India 40,000 R.O.I 104,000 R.O.I 39,000 France 84,000 Nepal 24,000 Romania 77,000 France 22,000 London 2014 South East 2014 Poland 185,000 Poland 94,000 India 127,000 India 50,000 Italy 97,000 R.O.I 44,000 R.O.I 94,000 France 23,000 France 93,000 China 22,000
23 Annual Population Survey (APS) - Office for National Statistics
acro.police.uk 37 14.15 Among the foreign national drug offenders, Jamaican nationals were the largest group and a large proportion of their offences related to drug supply. The data follows a similar trend for all three drugs types. Of the 1,580 offences, 1,178 (74.56%) related to the supply of drugs, which could be linked to already established drug production and supply routes as Jamaica is recognised as an important transit point for drugs being trafficked into the UK. It is likely that Jamaican crime groups help facilitate this drug trade by basing themselves in key European countries, such as the UK, Spain and the Netherlands. It is probable that Jamaican nationals are more dominant than any other Caribbean nationality in England and Wales due its historic links with the UK. The US Department of State acknowledges factors that contribute to Jamaica’s role, including the “country’s convenient geographic position as a waypoint for narcotics trafficked from Latin America; its lengthy, rugged, and difficult-to- patrol coastline; a high volume of tourist travel and airline traffic; its status as a major transhipment hub for maritime containerized cargo; inadequate educational and employment opportunities for at-risk youth who engage in crime.” 24
14.16 Analysis of the PNC data identified Poland, Portugal and R.O.I to be the top three offending EU nationalities. Additional analysis of the population statistics identify Poland with the largest population and R.O.I as the third largest non-British population living in England and Wales by nationality. It could be assumed that the largest populous groups in England and Wales leads to an increased level of offending.
14.17 Of interest, Portugal placed fifth overall making it the second highest EU FNO for drugs offences after Poland. Analysis identified that Portuguese nationals were linked to a higher number of heroin offences in comparison to offences involving cocaine or crack cocaine.
14.18 It is possible that those FNO recorded as Portuguese may in fact be from India as there is a provision in Portuguese nationality law that enables Indian nationals to become EU residents if they were born before 1961 in areas which were once Portuguese colonies such as, Goa, Daman and Diu. Over half of the 54,000 Portuguese citizens to enter the UK in the first quarter of 2015 were in fact from India.25 It is inferred that heroin is being trafficked into the UK via Portugal by Indian-born Portuguese nationals as their home country of India is known to be used as a hub for the transhipment of heroin originating from Afghanistan.
14.19 Geographical analysis identified that the Portuguese nationals have a disproportionate conviction rate in the eastern region of the UK, particularly in the Cambridgeshire police force area, accounting for over a quarter (26.96%) of FNO offences, followed by Lithuanian nationals with 10.29%. Whereas, in the West Yorkshire force area, Pakistani nationals account for over a third (49.61%) of drugs offences. The higher incidence of drug related crime from these nationals can be reasonably expected due to the higher population density of both Pakistan and Portuguese nationals in these particular regions.
24 International Narcotics Control Strategy Report, Volume 1, Drug and Chemic54al Control, March 2015. Available at https://www.state.gov/documents/ organization/239560.pdf39 25 http://www.migrationobservatory.ox.ac.uk/resources/commentaries/recent-trends-in-eu-nationals-born-inside-and-outside-the-eu/
38 Criminal record analysis to support the European Pact on International Drug Trafficking 14.20 However, research has found no clear evidence of a causal impact of immigration on crime in England and Wales. In support of this, Jamaicans and Somalians do not feature in the top five of foreign born nationals residing in England and Wales, but were the top two nationalities with the highest drug offending prevalence rate. In contrast, despite India having a high proportion of the foreign born population in the UK, the prevalence rates were lower than the prominent offending nationalities, Jamaica and Somalia.
14.21 There is a disproportionate number of Somalians and Jamaican drug offenders in the Avon and Somerset force area, accounting for 42.90% of all offences within that area. Avon and Somerset Police reported in their ‘Crime Needs Assessment’ that alongside the long-standing communities from the Caribbean and Pakistan, Bristol has seen large increases in its Somali residents over recent years26 which could account for an increased level of offending from these particular nationalities.
14.22 Between 2011 and 2014 a large proportion of drug offences by foreign nationals were committed in the Metropolitan Police Service (MPS) area, accounting for over half (52.79%) of all offences in England and Wales. Further analysis indicated that although significantly lower than MPS, drugs offences remained high for the following force areas, West Yorkshire, Greater Manchester Police (GMP), Avon and Somerset, Thames Valley Police (TVP), Essex, West Midlands Police (WMP), Hertfordshire and Sussex as shown in figure 14.5. It could be inferred that the majority of these force areas have a higher incidence of drug offences as they host key entry points for drug trafficking into the UK, including international airports, good rail transport links and for some, maritime ports. All factors that could be identified as critical links to drug dealing enterprises.
Figure 14.5 - Top ten police forces recording drug offences (2011 - 2014)
Police force Number Percentage
Metropolitan Police Service 6,097 52.79%
West Yorkshire 387 3.35%
Greater Manchester Police 372 3.22%
Avon & Somerset 359 3.11%
Thames Valley Police 334 2.89%
Essex 325 2.81%
West Midlands Police 308 2.67%
Hertfordshire 304 2.63%
Sussex 284 2.46%
Kent 215 1.86%
26 http://www.avonandsomerset-pcc.gov.uk/Document-Library/TERM-ONE/Police-and-Crime-Plan/Police-and-Crime-Plan/AS-PCNA-December-2015.pdf
acro.police.uk 39 14.23 Of the three drug types, analysis showed that cocaine is the drug most often associated with offences for which foreign nationals are convicted in England and Wales, with cocaine accounting for 45.35% of the total FNO offence count, followed by heroin (35.19%) and crack cocaine (19.46%) which is reflected in seizure data reported to the EMCDDA27 by the UK.
14.24
Figure 14.6 - Top ten nationalities involved in drug offences committed in England and Wales (2011-2014)
2000
1500
1000
500
0 l a d n a .I ia ia ia n ic alia n ta g n d n w a la is tu .O a In a o m om o k r R u lb n a S P a o ith A nk J P P L U
Class A - cocaine Class A - crack cocaine Class A - heroin
14.25 Figure 14.6 displays the top ten nationalities convicted in the UK for drugs offences. Analysis identified how certain nationalities are disproportionately linked to either cocaine, crack cocaine or heroin. For example, Polish, R.O.I and Albanian nationals were all predominantly linked to cocaine offences.
14.26 In contrast, nationals from Southern Asia (India and Pakistan) were associated with higher levels of heroin. There are a number of reasons that could account for this; either their proximity to source countries and major trafficking routes or familial links in the home country provide another resource to traffick drugs directly to the UK by posting packages via air or maritime methods. In support of this, the EMCDDA recognise that “familial links between British-based Asian and Pakistani criminals is a problem for the UK with heroin sent directly by parcel, air courier, air passenger or maritime container.” 28
14.27 The crack cocaine trade in England and Wales is largely influenced by Jamaicans and Somalians, followed by Pakistani nationals predominantly in the West Yorkshire force area. The ACRO Strategic Threat Assessment (2016) confirms “over the last two decades Jamaican OCG have been central in the advent of the UK’s crack cocaine market”.
27 http://www.nta.nhs.uk/uploads/uk-focal-point-report-2014.pdf 28 http://www.emcdda.europa.eu/attachements.cfm/att_239716_EN_UKFPannualreport2014.pdf
40 Criminal record analysis to support the European Pact on International Drug Trafficking 14.28 Overall, Jamaican nationals appear to dominate the drug markets across all three drug types, with the majority of offences relating to supply. Jamaica remains an important transhipment route particularly for cocaine produced in South America and destined for the UK market. Somalia, R.O.I, Poland and Portugal also consistently feature in the top ten for all three drug types as shown in figure 14.7.
Figure 14.7 - Top ten countries involved in drug offences committed in the UK by drug type
Cocaine Crack Cocaine Heroin
Country Number Country Number Country Number
Jamaica 419 Jamaica 614 Jamaica 547
R.O.I 326 Somalia 234 Somalia 327
Albania 322 Pakistan 147 India 261
Unknown 313 Portugal 94 Pakistan 245
Poland 294 Nigeria 64 Portugal 231
Somalia 242 India 64 Poland 198
Italy 194 R.O.I 61 Lithuania 187
Lithuania 188 Bangladesh 56 Bangladesh 163
Portugal 181 Poland 54 R.O.I 116
Romania 132 Italy 39 Latvia 112
14.29 The top three countries per drug type were categorised as follows:
Figure 14.8 - England and Wales cocaine offences by category
500
400
300
200
100
0 Jamaica R.O.I Albania
Possession Supply
acro.police.uk 41 14.30 Both Jamaica and Albania dominate the cocaine supply market in England and Wales and do so as they are linked to already established drug production and supply routes. Research reports that both Albania through the southern branch of the Balkan route29 and Jamaica remain important transit points for drugs being trafficked into Europe.30
14.31 Of note, R.O.I is placed second for the highest number of offences relating to cocaine, of which a high number are linked to possession (84.66%) as opposed to supply (15.34%). The proximity of R.O.I to the UK could account for the high proportion of R.O.I offenders in the UK but it remains unclear why the large majority of R.O.I nationals are convicted of possession rather than supply of cocaine.
14.32 Of interest, Albania is placed third for the highest cocaine offence count, but drops to 25th position for heroin. Overall, Albania remains an important transit point for shipments of cocaine and heroin destined for the European markets. There is evidence of increasing involvement by Albanian nationals in the cocaine market as the European cocaine network now consists of linkages between Colombian cocaine trafficking organisations with various criminal groups, including Albanian, Italian and French criminal organisations.31 This is reflected in the MPS force area with the number of offences involving Albanian nationals which increased from 34 offences in 2011 to 61 offences in 2014 in this area alone.
Figure 14.9 - England and Wales crack cocaine offences by category
800
700
600
500
400
300
200
100
0 Jamaica Somalia Pakistan
Possession Supply
29 http://www.balkaninsight.com/en/article/balkans-remain-major-drug-transit-point-us-report-03-03-2016 30 http://www.emcdda.europa.eu/publications/eu-drug-markets/2016/online/cocaine/trafficking-and-supply 31 ‘Cocaine Trafficking in Latin America, EU and US Policy Responses. Available at https://books.google.co.uk/books?id=F1k3DAAAQBAJ&pg=PA53&lp g=PA53&dq=albanian+nationals+in+the+uk,+increasing+involvement+of+the+supply+of+cocaine&source=bl&ots=3Ya-1FVqye&sig=0-GnMfVpHxeD CbKkFGehCvmaOgM&hl=en&sa=X&ved=0ahUKEwiKlaOnipzQAhWHBcAKHULJCFkQ6AEINzAF#v=onepage&q=albania&f=false
42 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 14.10 - England and Wales heroin offences by category
600
500
400
300
200
100
0 Jamaica Somalia India
Possession Supply
14.33 Somalia is placed second for both crack cocaine and heroin. A UNODC report highlights the growing importance of Africa as a transit area for Afghan heroin destined for Europe, supported by an increase in seizures particularly in Eastern Africa.32
14.34 Indian nationals are placed third in relation to heroin offences (figure 14.10), after Jamaicans and Somalians. India has become a hub for the transhipment of heroin originating from the Afghanistan region due to its proximity to the ‘Golden Crescent’,33 the largest producer of heroin in the world. UNODC reports that Afghanistan produces approximately 90% of the global heroin,34 it is then trafficked from Central Asia through Russia and the Baltic countries providing entry into the EU. Of note, Pakistan nationals had the fourth highest heroin count, of which a high number of offences are linked to supply (74.29%) rather than possession offences (25.71%). The UK Drug Policy Commission identified that a large proportion of Afghan heroin seized in the UK arriving via the sea and airports in South East England comes directly from Pakistan35 and EMCDDA recognise that Pakistani OCG appear to be playing an increasingly important role in facilitating heroin shipment to the EU, using established businesses in Pakistan and the EU which are used as fronts for heroin operations enabling them to traffic large quantities of drugs using various transportation methods including containers, couriers and postal parcels.36
14.35 Analysis identified that some police force areas are disproportionately high for cocaine offences in comparison to heroin and crack cocaine offences. This trend is clearly evident in the Northumbria region with 117 (90%) offences relating to cocaine and only three crack cocaine and ten heroin offences. A similar trend can be seen in the City of London and Hertfordshire force areas, being 90.59% and 63.16% respectively.
32 https://www.unodc.org/documents/wdr2015/World_Drug_Report_2015.pdf 33 The ‘Golden Crescent’ is a mountainous area, of Iran, Afghanistan and Pakistan where opium is grown. This area has been the main source of supply of heroin to the UK. 34 https://www.unodc.org/documents/data-and-analysis/tocta/5.Heroin.pdf 35 UKPDC, UK Drug Policy Commission, tackling Drug Markets and Distribution Networks in the UK 36 http://www.emcdda.europa.eu/publications/eu-drug-markets/2016/online/heroin/trafficking-supply acro.police.uk 43 14.36 In terms of gender, males have a higher prevalence rate for drug offences in the UK. Overall, the majority of offences (94.72%) related to male FNO.
14.37 The peak age range for FNO convicted for drugs offences in the UK are persons aged between 20 - 39 years of age.
ECRIS Notifications Out
14.38 The ECRIS NO analysis is based on conviction information sent from the UKCA to other MS. This section provides data and analysis for those notifications with a final conviction in either 2013 or 2014 relating to cocaine (including crack) and heroin.
14.39 The information that is exchanged between countries can help inform the picture of foreign national offending in the UK. This has been achieved by analysing those MS in which the notification has been sent.
14.40 Analysis of the ECRIS NO confirms many of the findings from the previous PNC analysis, particularly in relation to age and gender.
14.41 The UK sent 929 offence notifications relating to 1,312 cocaine (including crack) or heroin offences with a conviction date of 2013 or 2014. The top ten countries accounted for 84.60% of the total notifications sent. Analysis identified that Portugal received the highest number of notifications from the UK, followed by Poland, Lithuania and R.O.I. At the time of writing this report, Portugal is not currently connected to the UK (or any other MS) through ECRIS, but it is reported to receive the highest number of notifications from the UK as the count includes those notifications that have been sent manually.
14.42
Figure 14.11 - Top ten Member States receiving NO from the UK
Member States Number Percentage
Portugal 182 13.87% Poland 168 12.80% Lithuania 160 12.20% R.O.I 132 10.06% Netherlands 123 9.38% Latvia 88 6.71% Italy 73 5.56% Romania 69 5.26%
Czech Republic 61 4.65% France 54 4.12%
44 Criminal record analysis to support the European Pact on International Drug Trafficking 14.43 Comparative analysis with the PNC data reveal some inconsistencies in the ‘top four’ countries. Although the same four countries are present in both the PNC and ECRIS NO data, the order in which the countries are placed differs. The PNC data features Poland, Lithuania, Portugal and R.O.I as the top offending nationalities whereas analysis of the ECRIS data highlighted Portugal, Poland, Lithuania and R.O.I as the top four countries to receive notification offences from the UK. There are known data entry issues in PNC which may affect the data quality that could account for this difference. Further work is required to fully understand why this difference occurs.
14.44 Overall, offences were almost evenly split between the possession (56.25%) and supply (43.60%) of cocaine, crack cocaine or heroin, with very few relating to the manufacture of drugs (0.15%).
14.45 Further analysis of the top ten MS showed that the majority of drug offences by people of EU nationality were linked to drug possession. However, in the case of the Dutch, Portuguese and French nationals the majority of convictions were for supply.
Figure 14.12 - Top ten Member States to receive a NO from the UK by category
200
150
100
50
0 al d ia s ia ly ia e g n n .I d n lic c la a .O n atv Ita a ub n rtu o u R rla L m p ra o P ith e o e F P L th R e h R N c ze C
Possession Supply Manufacture
14.46 Further analysis of the data relating to The Netherlands and Portugal identified approximately half of the drugs supplied related to heroin, being 51% and 48.65% respectively. Both The Netherlands and Portugal are recognised as key entry points for drugs entering Europe. In support of this, the NCA identified the Netherlands as a key country for organising the importation of heroin into the UK drugs market.37
37 http://www.nationalcrimeagency.gov.uk/crime-threats/drugs acro.police.uk 45 Figure 14.13 - Top ten Member States to receive a NO from the UK by drug type
200
150
100
50
0 al d ia s ia ly ia e g n n .I d n lic c la a .O n atv Ita a ub n rtu o u R rla L m p ra o P ith e o e F P L th R e h R N c ze C
Class A - cocaine Class A - crack cocaine Class A - heroin
14.47 Notably, a large number of notifications sent to Latvia and Czech Republic were linked to heroin. EMCDDA recognise both these countries as important transit hubs (via the Balkan route) for heroin trafficking in Europe.38 In contrast, R.O.I was disproportionately high for notifications relating to cocaine (58.33%), in comparison to heroin (23.48%) or crack cocaine (18.18%). In 2016, the ‘EU Drug Markets Report’ compiled by the EMCDDA and Europol, reported that Irish OCG have connections with drug cartels in South and Central America which facilitates the direct importation of cocaine into Ireland.39
ECRIS Notifications In
14.48 The ECRIS NI analysis is based on conviction information received by the UK from a MS referring to the convictions of a UK national in their country. This section provides data and analysis for those notifications with a conviction in either 2013 or 2014 relating to cocaine (including crack) and heroin.
14.49 The UKCA received fewer offence notifications from EU MS in 2014 in comparison to 2013, which is largely attributed to a 30.77% decrease in the number received from France. This reduction does indicate a decrease of UK nationals offending in France in 2014, but it is more likely that a full and historic exchange between the UK and France creates the influx of notifications in 2013, addressing a backlog in 2012 and 2013 before resuming normal practice in 2014.
38 Latvia and Czech Republic country overview, available at http://www.emcdda.europa.eu/countries 39 European Monitoring Centre for Drugs and Drug Addiction and Europol (2016), EU Drug Markets Report: In-Depth Analysis, EMCDDA–Europol Joint publications, Publications Office of the European Union, Luxembourg.
46 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 14.14 - Top ten NI countries
Convicting Country Number Percentage
France 594 35.06% R.O.I 258 15.23% Spain 209 12.34% Netherlands 182 10.74% Germany 169 9.98% Cyprus 99 5.84% Belgium 45 2.66% Italy 40 2.36%
Sweden 25 1.48% Denmark and Austria 20 1.18%
14.50 Analysis of the NI data identified that UK nationals were convicted of drug related offences across 16 different MS, predominantly in France (35.06%), followed by R.O.I (15.23%) and Spain (12.34%). Further analysis of the offences committed by UK nationals in R.O.I identified that UK nationals are predominately linked to possession offences in R.O.I rather than the supply, importation or trafficking of drugs.
14.51 The large majority of notifications received from MS relate to ECRIS common category “offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors not exclusively for own personal consumption”, suggesting that a large majority of UK nationals are convicted in Europe for trafficking offences. It is important to note that analysis of ECRIS common categories is limited as each MS will classify drugs offences differently and therefore analysis concerning common categories should be treated with caution.
14.52 Figure 14.15 - NI received by the UK by category
Common Category Number
Offences related to illicit trafficking in narcotic drugs, psychotropic substances and 737 precursors not exclusively for own personal consumption
Offences related to drugs or precursors, and other offences against public health 642
Illicit consumption of drugs and their acquisition, possession, manufacture or 227 production exclusively for own personal consumption
Manufacture or production of narcotic drugs not exclusively for personal consumption 77
Aiding or inciting others to use narcotic drugs or psychotropic substances illicitly 11
14.53 A large majority of UK offenders are males (90.89%) aged between 20 – 39 years of age.
acro.police.uk 47 15 Spain
15.1 The project team sourced the following data:
Data Source Type Date Parameters
ECRIS NO 2013 - 2014
ECRIS NI 2013 - 2014
National system 2011 -2014
15.2 Due to legislative constraints, Spain are unable to distinguish the drug type or category of offence, for example, cultivation, possession and supply. Therefore, the analysis on the Spanish data is not limited to cocaine, crack cocaine or heroin and instead relates to all drugs.
15.3 Offence location is not typically recorded at the crime reporting stage and as a result the project team have used the court address as an indicator of offence location as the local courts judge the minor crimes committed within their province. However, it is important to note that main cases of drugs trafficking committed by organised groups and drugs offences committed abroad are judged in the Central Court in Madrid. For instance, those offences whereby a person has been arrested at an international airport in Spain for attempting to enter the country with illicit drugs are judged at the Central Court in Madrid. This limits the project team in identifying potential hotspots as not all offences are judged in the local province to which the offence was committed. It is important to note this caveat for the geographical analysis that follows in this section.
15.4 Spain is not known for producing drugs, however due to its geographical location it is an important gateway country for transiting drugs, notably cocaine. Given its nature as a transit country, Spain has the highest amount of cocaine seizures within Europe. It is important to note that The Netherlands does not feature in the seizure statistics as no data was submitted to EMCDDA for 2014. According to the 2014 EMCDDA drug seizure figures, approximately, 45.08% of the cocaine seized in the EU was intercepted in Spain, followed by 19.32% seized in Belgium and 4.30% in France.
15.5 In Spain, a total of 66,850 offences were committed by Spanish nationals and FNOs between 2010 and 2014 relating to the five common ECRIS categories. A total of 13,121 offences were removed from the dataset as the offences were either deemed not relevant to the project (e.g. medicinal offences or doping) and/or the conviction date sat outside the project date parameters (pre-2011). 53,729 offences remained in the final dataset relating to both Spanish and FNO.
48 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 15.1 - National offence data for Spain (2011 - 2014)
National System Total Spanish EU FNO Non EU FNO Unknown
Offences 53,729 30,237 3,392 20,004 96 % 100% 56.28% 6.31% 37.23% 0.18%
15.6 From 2011 – 2014, over 140 different nationalities were convicted in Spain. Analysis of the Spanish data shows that 56.28% (30,237) of offences were committed by Spanish nationals. Foreign EU nationals accounted for 6.31% (3,392) whereas Non EU nationals accounted for 37.23% (20,004) and the remaining 0.18% (96) were unknown (figure 15.1).
15.7 A comparison between Spanish and all other nationalities reveals that 43.54% of the drugs offences in Spain were committed by foreign nationals as shown in figure 15.2.
Figure 15.2 - Comparison between Spanish and FNO convicted in Spain for drugs offences
Unknown (0.21%) Spain (56.28%)
Morocco
Colombia
FNO (43.54%) Dominican Republic Romania Nigeria Gambia Pakistan Senegal Portugal Ecuador
Other (132 Nationalities)
15.8 Unless otherwise stated, all Spanish nationals have been excluded from the subsequent country analyses. On removal of the Spanish nationals 23,492 offences remained.
15.9 From 2011 to 2014 there was an 8.80% reduction of drug related offences committed by FNO in Spain. The decrease could be attributed to one or more reasons including reduced availability, the effects of law enforcement activity, or competition with other drugs, such as NPS.40 It could also be inferred that the decrease could be accountable to the measures taken by the Spanish authorities in 2014 to strengthen the border control of the Spanish provinces in Morocco; Melilla and Ceuta.41
40 European Monitoring Centre for Drugs and Drug Addiction (2015), New psychoactive substances in Europe. An update from the EU Early Warning System (March 2015), Publications Office of the European Union, Luxembourg. 41 https://www.theguardian.com/world/2014/mar/06/spain-security-717morocco-territories-immigration acro.police.uk 49 15.10 Figure 15.2 displays the top foreign nationalities to be convicted for drugs offences. The listed countries in figure 15.2 account for 72.11% of the total foreign offence count.
15.11 There is a significant difference in the volume of nationalities with the highest offending rates. Moroccans feature strongly (8,788), with Colombians (2,719) in second place, followed by nationals from the Dominican Republic (1,125) which is significantly lower in volume than first place.
15.12 Figure 15.3 identifies that in Spain, Morocco and Romania have the largest foreign born population. Of note, both Morocco and Romania feature as the most prolific EU and Non EU nationals in Spain, suggesting a link between the size of foreign communities in Spain and the volume of offending that may be attributable to them.
Figure 15.3 - Variation of the foreign population resident in Spain in 2014 by nationality42
Nationality 2014 Percentage
Total population 46,512,199 100%
Spain 41,835,140 89.94%
Top Foreign Nationals 4,677,059 10.06%
Other 1,329,352 2.86%
Romania 728,253 1.57%
Morocco 717,992 1.54%
UK 310,052 0.67%
Ecuador 214,039 0.46%
Italy 180,823 0.39%
Colombia 173,193 0.37%
China 165,978 0.36%
Germany 148,502 0.32%
Bulgaria 139,931 0.30%
Bolivia 127,477 0.27%
Portugal 108,984 0.23%
France 99,486 0.21%
Ukraine 81,802 0.18%
Argentina 80,923 0.17%
Poland 70,272 0.15%
42 Population figures by Instituto Nacionel de Estadistica, available at http://www.ine.es/en/prensa/np917_en.pdf
50 Criminal record analysis to support the European Pact on International Drug Trafficking 15.13 As stated previously, Moroccan nationals account for 37.41% of the total foreign offence count in Spain. It is well documented that Morocco is Europe’s main supplier in cannabis,43 therefore it is not surprising that Spain due to its close proximity to Morocco is the main entry point for cannabis. Different nationalities exploit Morocco’s well established drug route to traffic not only cannabis but also cocaine and heroin into Spain for onward distribution to Europe. One of the main points of entry to Spain from Morocco is the city of Algeciras, a port city only 14 kilometres from northern Morocco. It is assumed that drug courier’s take advantage of the frequent ferry connections connecting Morocco to Algeciras.
15.14 Colombians are placed second accounting for 11.57% of all offences committed by foreign nationals. This may be related to the drug route whereby Colombia is a source country and Spain is one of the destination countries. Spain serves as a natural springboard for Colombia-based OCG looking to move cocaine into other parts of Europe as there is already a sizeable Colombian population (173,193) in Spain and there is no language barrier.
15.15 Of the European countries in the top ten, both Romania and Portugal are represented. The strategic positioning of both Portugal and Romania could account for the high volume of Romanian and Portuguese offending in Spain as both countries sit on key drugs transit routes for entry into Europe.
15.16 The greatest percentage of drugs convictions occur in Madrid, followed by Ceuta, Barcelona and Algeciras. It is understood that either shipping containers move drugs through the ports of Barcelona, Ceuta or Algeciras or it is carried through the international airports by drug couriers flying into the country. Additional transport links make these cities more accessible to traffic drugs for onward distribution to the UK and the rest of Europe.
15.17 Although the limitations of using the court address have been cited, analysis identified that Madrid remains as a hotspot even after discounting those offences that were heard at the Central Court.
43 International Narcotics Control Strategy Report, Volume I, Drug and Chemical Control, March 2015
acro.police.uk 51 Figure 15.4 - Top four hotspots in Spain by court address
EMCDDA report the number of seizures occurred at airports, Barcelona hosts Spain’s second busiest airport accounting for a especially at Madrid-Barajas airport as it is an important entry large number of drug offences. It is also a port city which connects point to the EU from South America.44 Spain with Ibiza, Menorca, Mallorca, Morocco and Sardinia.
Algericas is a city lying on Europe’s southernmost border and is considered a main gateway for drugs trafficking according to the EMCDDA. The port here is the gateway to South America and Africa. Its close proximity to Morrocco makes it an attractive entry point for drugs entering the EU. Ceuta is an autonomous city of Spain, located on the North Africa coast. The two Spanish enclaves in North Africa; Ceuta and Melilla are recognised as major conduits for drug smuggling, moving cocaine towards the lucrative markets of the EU.
15.18 According to a Eurostat45 report published in 2015, both Andalucía, bordering Spain’s southern coast and Melilla regions were registered with the highest unemployment areas in Spain. Unemployment indicates a loss of income for individuals or families resulting in an increase in pressure to raise money in other ways in order to support themselves and their family. Previous research46 shows a relationship between high unemployment figures with a high drug prevalence rate. It could be inferred that the high unemployment rate in the southern region of Spain may lead to drugs trafficking in order to supplement the loss of income.
15.19 The peak age range for FNO convicted for drugs offences in Spain are for persons aged between 20 - 39 years of age.
44 http://www.emcdda.europa.eu/attachements.cfm/att_228526_EN_EMCDDA_NR2013_Spain.pdf 45 http://ec.europa.eu/eurostat/statistics-explained/index.php/Unemployment_statistics_at_regional_level 46 http://www.12keysrehab.com/blog/drug-abuse-and-unemployment
52 Criminal record analysis to support the European Pact on International Drug Trafficking 15.20 From 2011 to 2014, the Spanish data reveals that male FNO show a higher involvement in drug offences overall, accounting for 89.66% of the total foreign offence count. The top offending FNO nationalities for males in order of magnitude are Morocco (8,364), Colombia (2,157) and Dominican Republic (930). In contrast, the top offending nationalities for females are Colombians (562), Moroccans (424) and nationals from the Dominican Republic (195). Although the same three countries are present for both gender groups, the proportionality for gender and nationality differ somewhat.
15.21 As shown in figure 15.5, the top ten countries of nationality differ quite significantly dependant on whether the offence was committed by the male or female cohort. For example, in Spain, nationals from Latin American countries are heavily represented in relation to female offending, in contrast male offending in Spain is largely committed by Moroccans and Colombians followed by nationals that are evenly distributed between the Caribbean, Europe and South Africa. Research identifies a clear correlation between crime and nationality with drug trafficking being the most common conviction among women from Latin America, particularly those from Colombia.47 UNODC report that women disproportionately act as drug mules, where they are forced to swallow or insert drugs into their bodies as a means of transporting them out of the country.48
15.22 Figure 15.5 - Top ten country of nationality by gender
Nationality Male Nationality Female
Morocco 8,364 Colombia 562 Colombia 2,157 Morocco 424 Dominican Republic 930 Dominican Republic 195 Romania 677 Romania 143 Nigeria 618 Bolivia 123 Gambia 600 Ecuador 120 Pakistan 594 Brazil 116 Senegal 581 Portugal 89
Portugal 474 Paraguay 58 France 446 Venezuela 52
15.23 The extent of drug use among men and women varies from country to country. Of interest, the gender gap shrinks when data on South American nationalities is considered, specifically in relation to Colombians, Ecuadorians, Brazilians, Paraguayans, Chileans and Guyanese nationals. Paraguayan females for example, account for 58 (42.96%) of all Paraguayan offences committed in Spain, with 77 (57.04%) offences attributed to the male cohort.
47 https://www.law.ox.ac.uk/research-subject-groups/centre-criminology/centreborder-criminologies/blog/2015/05/experiences 48 https://www.unodc.org/documents/ungass2016/Contributions/UN/Gender_and_Drugs_-_UN_Women_Policy_Brief.pdf.
acro.police.uk 53 15.24 Social exclusion, poverty and gender based violence are the three main reasons why women get involved in drugs trafficking. Women are often seen as good recruitment targets by traffickers as stereotyped perceptions of older women are non-threatening and pregnant women are thought to arouse less suspicion. Women as ‘drug mules’ are made to swallow or insert drugs into their bodies and are often misled about the quantities that they are carrying.
15.25 Analysis of EU nationals by gender confirms the trend that males are more frequently involved in drug offences in Spain. Interestingly, the proportion of female offenders increase in regards to Polish women who account for over a quarter (28.43%) of the 102 offences committed by Polish nationals in total. It is not known why this gender gap narrows particularly in relation to Polish women. More research is needed internationally in order to clarify why these differences and patterns emerge in drug use among males and females.
ECRIS Notifications Out
15.26 The ECRIS NO analysis is based on conviction information sent from the Spanish CA to other MS. This section provides data and analysis for those notifications with a final conviction in either 2013 or 2014.
15.27 Spain sent 1,311 offence notifications with a final conviction date between 2013 or 2014. The top ten countries accounted for 94.89% of the total offence count.
15.28 Analysis identified that a large number of notifications were sent to Romania, followed by France then Italy.
Figure 15.6 - Top ten NO countries by nationality
Nationality Number Percentage
Romania 343 26.14% France 234 17.84% Italy 199 15.17% UK 135 10.29% Holland 90 6.86% Germany 68 5.18% Bulgaria 60 4.57% Poland 50 3.81% Lithuania 35 2.67% Belgium 31 2.36%
15.29 Comparative analysis between the National and ECRIS dataset identified similar nationality trends with exception to Portugal. This is because Portugal are not yet in the position to participate in automated exchange of criminal records via ECRIS.
54 Criminal record analysis to support the European Pact on International Drug Trafficking 15.30 Analysis of the sanction data identifies a large proportion of drugs offences (99.16%) were sentenced to imprisonment. Small amounts of drugs are considered personal use and it is not generally considered for criminal proceedings. As a result, the Spanish dataset contains the more serious offences. This could explain the high proportion of imprisonment sanctions.
15.31 Analysis of the ECRIS NO data confirms many of the findings from the analysis of the national data, particularly in relation to age and gender.
ECRIS Notifications In
15.32 The ECRIS NI analysis is based on conviction information received by Spain from a MS referring to the convictions of a Spanish national in their country. This section provides data and analysis for those notifications with a final conviction in either 2013 or 2014 relating to the five ECRIS common categories.
15.33 Spain received 1,764 notification offences with a final conviction date of either 2013 or 2014. The number of offences increased by 10.25% from 2013 to 2014 as Spain started to exchange with more countries.
15.34 Spanish nationals were convicted of drug related offences across 16 different MS, predominantly in France (56.75%), followed by Germany (14.91%) and UK (7.77%), receiving a monthly average of 42 notifications from France, 11 from Germany and six from the UK.
Figure 15.7 - Top ten NI countries
Nationality Number Percentage
France 1001 56.75% Germany 263 14.91% UK 137 7.77% Italy 122 6.92% Belgium 95 5.39% Netherlands 36 2.04% Sweden 24 1.36% Austria 23 1.30% R.O.I 17 0.96% Luxembourg 11 0.62%
15.35 The large majority of notifications received by MS relate to the ECRIS common category; “offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors not exclusively for own personal consumption”, suggesting that a large majority of Spanish nationals are convicted in Europe for trafficking offences. However, it is important to note that analysis of ECRIS common categories is limited as each MS will classify drugs offences differently.
acro.police.uk 55 15.36
Figure 15.8 - NI received by Spain by category
Common category Number
Offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors not 1,234 exclusively for own personal consumption
Illicit consumption of drugs and their acquisition, possession, manufacture or production exclusively 383 for own personal consumption
Offences related to drugs or precursors, and other offences against public health 110
Aiding or inciting others to use narcotic drugs or psychotropic substances illicitly 36
Manufacture or production of narcotic drugs not exclusively for personal consumption 1
15.37 Of those Spanish nationals convicted throughout Europe, the large majority are male between the ages of 20 – 39.
56 Criminal record analysis to support the European Pact on International Drug Trafficking 16 Lithuania
Data Source Type Date Parameters
ECRIS NO 2013 - 2014
ECRIS NI 2013 - 2014
National system 2011 -2015
16.1 The Lithuania national criminal record dataset includes both offence location and drug type therefore offences related to any other drugs do not form part of the analysis in this section, unless otherwise stated.
16.2 The geographical location of Lithuania encourages the international activity of OCGs due to its external border with Belarus on the east and the Kaliningrad region of Russia on the southwest. Lithuania is considered a transit country for the trafficking of illicit drugs between eastern and western Europe. The EMCDDA report that heroin enters Lithuania from central Asia via Russia and Belarus. Whereas, cocaine is imported in different ways, by sea from South America, by land from the Netherlands and via air or postal items. The EMCDDA further report that foreign and local crime groups employ Lithuanian nationals as drug couriers to transit cocaine from South or Central America into Europe or from one EU country to another. It is reported that the cocaine that is smuggled by Lithuanian nationals is intended for drug markets in the UK, the Netherlands or Belgium.49
16.3 According to the EMCCDA seizure statistics, cocaine seizures varied greatly. In 2011 approximately 10kg of the substance was seized which increased to 120kg in 2012, decreasing again to approximately 3kg in 2013 rising in 2014 to 116kg. In contrast, heroin seizures remained quite low in comparison to other EU MS throughout the four years (2011 – 2014) with 2013 reported to be the year with the largest amount seized with 13kg.
16.4 In Lithuania, there was a total of 1,746 cocaine and/or heroin offences committed by Lithuanian nationals and FNO between 2011 and 2014.
Figure 16.1 - National offence data for Lithuania (2011 - 2014)
Total Lithuanian EU FNO Non EU FNO Unknown
Offences 1,746 1,665 8 31 42 % 100% 95.36% 0.46% 1.78% 2.40%
49 EMCDDA, Lithuania National Report (2013), New Development, Trends and In-depth Information on Selected Issues
acro.police.uk 57 16.5 Analysis identified a very small number of EU FNO committing cocaine and/or heroin related offences in Lithuania. Across four years (2011–2014) only six Latvian, one Dutch and one Portuguese national were convicted of drugs offences. Similarly, very few Non EU nationals are represented in the national data. Reviewing the same yearly parameters, only 31 offences were committed by Non EU FNO. The remaining 1,665 offences relate to Lithuanian nationals indicating a closed drugs market controlled by mainly Lithuanian OCG. For this reason, the subsequent analysis is based on all EU (including Lithuania) and Non EU nationals.
16.6
Figure 16.2 - Top offending nationalities convicted for cocaine/heroin offences in Lithuania (2011-2014)
Nationality Number
Lithuanian 1,665
Stateless 41
Russian 13
Georgian 6
Latvian 6
Nigerian 5
Kyrgyzstani 3
Icelandic 2
Dutch, Belorussian, Unknown, 1 each Azerbaijani and Portuguese
16.7 A high proportion (93.01%) of Lithuanian offences are linked to heroin in comparison to cocaine suggesting that heroin in Lithuania is more common than cocaine. However, EMCDDA seizure data does not support the Lithuanian data as the seizure statistics report that larger volumes of cocaine are seized as opposed to heroin. Further research is required to determine why this difference occurs.
16.8 Geographical analysis identified that Vilnius followed by Klaipeda and Kaunas are hotspots for both cocaine and heroin offences as shown in figure 16.3.
58 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 16.3 - Map identifying Lithuanian offence hotspots
16.9 As previously mentioned, the greatest percentage of heroin/cocaine offences occur in Vilnius, the capital city of Lithuania with a population of 532,762.50 The higher incidence of drug related crime in Vilnius could be attributed to; a high population density, additional transport links making these cities more accessible to traffic drugs for onward distribution or high prison populations in Vilnius’s Lukiskes Prison, as even OCG members that are in prison remain in the drug trade.
16.10 Over four years (2011 – 2014), approximately a third of all Lithuanian offences were linked to an address in a Roma village of the Kirtimai Tabor community in a territory of Vilnius city. This particular address is the only house that has been legally registered and as a result, a large majority of offences were connected to this specific address. The other 70 (approximate) houses within that community are not legally registered, as they have been constructed without the appropriate government authorisation.51 Further analysis identified that over half of the cocaine and/or heroin offences are transported from this Roma village to cities including; Vilnius, Visaginas, Klaipeda, Nemencine.
50 https://www.citypopulation.de/Lithuania.html 51 http://www2.ohchr.org/english/bodies/cerd/docs/AdvanceVersions/CERD-C-LTU-4_5.doc
acro.police.uk 59 16.11 Research indicates that the Roma community in Lithuania suffer exclusion from public life and the labour market as well as experiencing health and housing issues. It is inferred that social exclusion from the labour market may push the Roma community towards drug trafficking as a priniciple source of income. This is supported by United Nations (UN) who have identified that most of the adult Roma of the Kirtimai Tabor have been convicted for illegal possession of narcotic and psychotropic substances.52
16.12 Klaipeda is the second largest hotspot for drug related crime and is Lithuania’s third largest city. It’s located on the eastern coast of the Baltic Sea and is the only ferry port in the country. The port connects Lithuania to Russia, Belarus, Ukraine as well as Western Europe, South East Asia and the continent of America53 which could account for the large proportion of drug offences in this region.
16.13 Kaunas is the third largest hotspot for drug related crime and is Lithuania’s second largest city. It is served by a number of major highways, linking Kaunas to cities in Poland, Latvia and Estonia. Kaunas also hosts an international airport and good rail transport links, all factors that could be identified as critical links to drug dealing enterprises. Kaunas prison could also account for the increased level of offending in this area. Prison-based drug markets are structurally similar to those found in the wider community, it is an environment where drugs are in demand and are valuable as both currency and commodity. UNODC reported, drug use in prisons are highly prevalent with one in three persons incarcerated using drugs at least once.54 Further research is required to examine the dynamics and operation of supply routes and markets in a custodial setting as it appears little research has been done to date.
16.14 Analysis identified a few cases, whereby the offender was intercepted transporting drugs from Lithuania to Poland, Norway or Ireland or drugs were intercepted on entry to Lithuania from Russia, Belarus or from Central America, Costa Rica or South America, Bolivia or Peru.
16.15 In terms of gender, males have a higher prevalence rate for drug offences in Lithuania. Overall, the majority of offences (80.01%) related to males.
16.16 Analysis shows that persons from age 30 - 39 are predominantly inclined to commit an offence relating to cocaine or heroin or both.
ECRIS Notifications Out
16.17 Lithuania initially started exchanging ECRIS data with Austria and Latvia in April 2012, increasing to 19 more countries by the end of 2014.
52 United Nations, International Convention on Elimination of All Forms of Racial Discrimination, 31 May 2010 53 http://www.portofklaipeda.lt/the-port-of-klaipeda 54 https://www.unodc.org/documents/wdr2015/World_Drug_Report_2015.pdf
60 Criminal record analysis to support the European Pact on International Drug Trafficking 16.18 Analysis of the ECRIS NO data confirms that very few EU nationals were convicted of cocaine offences in Lithuania between 2013 and 2014. In total, eight notifications were sent, indicating a closed drugs market controlled by mainly Lithuanian OCG. As a result, there is insufficient data to enable further analysis of the Lithuanian NO data.
ECRIS Notifications In
16.19 The ECRIS NI analysis is based on conviction information received by Lithuania from a MS referring to convictions of a Lithuanian national in their country.
16.20 This section provides data and analysis for those notifications with a final conviction in either 2013 or 2014 relating to the five ECRIS common categories.
16.21 Lithuania received 908 notification offences from MS with a final conviction date of either 2013 or 2014. Lithuanian nationals were involved in drug offences across 17 different MS, largely the UK (monthly average of 20 notifications), followed by R.O.I (monthly average of seven notifications) and Germany (monthly average of seven notifications).
16.22 Figure 16.4 - Top ten NI countries
System Type Percentage
UK 483 53.19%
R.O.I 158 17.40%
Germany 70 7.71%
France 63 6.94% Spain 31 3.41%
Sweden 18 1.98%
Finland 16 1.76%
Denmark 12 1.32%
Latvia 11 1.21%
Italy 9 0.99%
acro.police.uk 61 16.23 Further analysis of the notifications received by Lithuania from the UK has identified that where the drug is known, Lithuanian nationals were predominantly linked to cannabis (27%), followed by heroin (15%) then cocaine (10%).
Figure 16.5 - NI offences received from the UK by drug type
Methadone (1%)
Mephedrone (1%) MDMA (2%) Unknown (1%) Crack Cocaine (3%)
Class C (6%)
Amphetamine (8%) Cannabis/Cannabis Resin (27%)
Class B (9%)
Class A (17%)
Cocaine (10%)
Heroin (15%)
16.24 The large majority of notifications received by MS relate to the ECRIS common category; “offences related to drugs and their acquisition, possession, manufacture or production exclusively for own personal consumption”, suggesting that a large majority of Lithuanian nationals are convicted in Europe for the possession or manufacture of drugs for their own personal consumption. However, it is important to note that analysis of ECRIS common categories is limited as each MS will classify drugs offences differently.
62 Criminal record analysis to support the European Pact on International Drug Trafficking 16.25
Figure 16.6 - NI received by Lithuania by common category
Common Category Number
Illicit consumption of drugs and their acquisition, possession, manufacture or production exclusively 329 for own personal consumption
Offences related to drugs or precursors, and other offences against public health 312
Offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors not 198 exclusively for own personal consumption
Manufacture or production of narcotic drugs not exclusively for personal consumption 37
Aiding or inciting others to use narcotic drugs or psychotropic substances illicitly 32
16.26 Of those Lithuanian nationals convicted throughout Europe, the large majority are male between the ages of 20 – 39.
acro.police.uk 63 17 Romania
17.1 The project team sourced the following data:
Data Source Date Parameters
National System 2011 - 2014
17.2 Romania were unable to provide ECRIS data and as a result the following analysis focusses only on the national data provided by the Romanian Central Authority.
17.3 Romania were unable to provide offence location as it is not stored within the national system as the national law does not contain such provisions. This information can be found on the court decision forms (paper forms). To retrieve this information the project team would have to rely on manual interaction of the court paper forms held at the Ministry of Justice (MoJ) and then manually transfer this data. However, it was not possible to access this information from the MoJ as our research did not fall under ‘criminal proceedings’.
17.4 Due to legislative constraints, Romania were unable to distinguish between drug type. Therefore, the analysis on the Romanian data is not limited to cocaine, crack cocaine or heroin and instead relates to all drugs offences.
17.5 EMCDDA report that the Romanian authorities seized 111.6kg of heroin in 2013 decreasing to approximately 26kg in 2014. A decline was also reported in the quantity of cocaine seized, from 161kg in 2011 to 34kg in 2014, while the number of seizures remains fairly constant over recent years. The decrease could be attributed to one or more reasons including reduced availability, the effects of law enforcement activity, or competition with other drugs, such as new psychoactive substances (NPS).
17.6 Due to its geographical position within the EU, Romania forms part of the Balkan route for heroin smuggling as it lies on the northern path of the Balkan route where it enters Romania from Afghanistan by land via the Ukraine, Moldova and Bulgaria, and by sea through the Black Sea port of Constanta.55 It is assumed that the drugs are then directed to markets with high consumption in Western Europe notably Germany, Austria, Netherlands and Switzerland.56 Romania also appears on the cocaine drug trafficking route as the drug is shipped in through the ports on the Black Sea from South America or by road or air from other MS intended for markets outside of Romania.57
55 https://www.unodc.org/documents/data-and-analysis/Studies/Illicit_DT_through_SEE_REPORT_2014_web.pdf 56 International Narcotics Control Strategy Report: Volume I: Drug and Chemical Control (2010) 57 http://www.emcdda.europa.eu/countries/romania
64 Criminal record analysis to support the European Pact on International Drug Trafficking 17.7 Between 2011 and 2014, 4,834 convictions were committed by Romanian and FNO .
Figure 17.1 - National offence data for Romania (2011 - 2014)
Total Romanian EU FNO Non EU FNO
Offences 4,384 4,244 28 112 % 100% 96.81% 0.64% 2.55%
17.8 Analysis identified a very small number of EU FNO committing drug related offences in Romania. Over four years (2011 – 2014) only 28 offences were committed by EU nationals and 112 by Non EU nationals. The remaining 4,244 offences relate to Romanian nationals. For this reason, the subsequent analysis is based on all EU (including Romanian) and Non EU nationals.
17.9
Figure 17.2 - Top offending nationalities convicted for drugs related offences in Romania (2011-2014)
Nationality Number
Romania 4,244 Turkey 26 Moldova 25 Italy 9 Germany 9 Bulgaria 8 Vietnam 7 Spain 6 Hungry 6 Nigeria 5 Albania 5
17.10 From 2011 to 2012 the number of offences increased significantly from 633 to 1,113, an increase of 75.83%. From 2012 the number of offences increased quite steadily year on year from 1,113 in 2012, 1,258 in 2013 and 1,380 in 2014. There has been no change in national law during this period to account for this difference. It is possible that the increase in criminality could be determind by social, economical aspects.
17.11 In terms of gender, males have a higher prevalence rate for drug offences in the Romania. Overall, the majority of offences (88.62%) related to males.
17.12 The peak age range for offenders convicted for drugs offences in Romania are for persons aged between 20 - 29 years of age.
acro.police.uk 65 18 Germany
18.1 Germany provided the project team with the following data:
Data Source Date Parameters
National System 2011 - 2014
18.2 Germany only retains the ECRIS NO data for one year after which it is deleted and so the data supplied to the project was sourced from the national system. Therefore, the following analysis focusses only on the national data and not ECRIS.
18.3 National data protection provisions resulted in Germany sharing only the year of birth and not the full date of birth. For this same reason the German CA were unable to provide data relating to Non EU nationals.
18.4 Germany were unable to provide the offence location as this information is not stored in the German criminal register, therefore the project team were unable to geographically map this data to a specific offence address. Instead the project team used the address of the local court (Amtsgericht) that dealt with the offence. This gave an approximate location as to where the offence occurred. However, it should be noted that the ‘catchment area’ can be large, especially in cases where the deciding court was a regional court (Langericht). Furthermore, there could be a few cases to which the court address did not match the offence address as the authority of the local court did not meet the seriousness of the crime and so the offence was trialled at a regional court. It is important to note these limitations in the geographical analysis that follows.
18.5 Germany is a consumer and transit country for illegal drugs but is not a significant drug production or cultivation country. Heroin is trafficked to Germany from South-West Asia, mainly from Afghanistan whereas, cocaine transits Germany from South America directly by sea or via airmail or air couriers.58 OCGs are heavily engaged in drugs trafficking in Germany, the 2015 International Narcotics Control Strategy Report (INCSR) states that, “German and Turkish organized crime groups continue to dominate the drug trade, with cannabis, cocaine and heroin making up the bulk of drugs smuggled into and through Germany.” 59
18.6 EMCDDA reports that Germany seized 498kg of heroin in 2011, decreasing to 242kg and 270kg in 2012 and 2013 respectively before increasing to approximately 780kg in 2014. Cocaine seizures followed a similar trend in that 1,941kg of cocaine was seized in 2011, decreasing to 1,258 and 1,315 in 2012 and 2013 respectively before increasing again to approximately 1,567kg in 2014. The seizure statistics in Germany indicate that cocaine is the main illicit drug seized.
58 http://www.emcdda.europa.eu/countries/germany 59 2015 International Narcotics Control Strategy Report, available at http://www.state.gov/j.inl/nrcrpt/2015/vol1/238971/html
66 Criminal record analysis to support the European Pact on International Drug Trafficking 18.7 In Germany, between 2011 and 2014, 16,755 offences were committed by EU FNO.
Figure 18.1 - National offence data for Germany (2011 - 2014)
Total German EU FNO Non EU FNO
Offences 16,755 Not provided 16,755 Not provided
18.8 The project team managed to acquire the specific drug type for a very limited number of offences, however this is not routinely recorded. Of the 16,755 German offences, 218 related to cocaine, 128 were linked to heroin and six offences related to both cocaine and heroin. The remaining 16,403 offences the drug type was unknown.
18.9 A significant amount of EU FNO groups operate in Germany. Figure 18.2 displays the top ten EU nationalities convicted of drugs offences, which account for 82.32% of the total EU foreign offence count. These countries consistently feature in the top ten in each of the four years.
Figure 18.2 - Top ten FNO involved in drugs offences in Germany (2011 - 2014)
Nationality Number Percentage
Italy 3,396 20.27% Poland 2,616 15.61% The Netherlands 1,760 10.50% Greece 1,128 6.73% France 1,084 6.47% Austria 827 4.94% Czech Republic 817 4.88% Croatia 759 4.53% Romania 715 4.27% Portugal 691 4.12%
18.10 Research shows that Germany is the most populous country in the EU with an estimated 82 million living there. Over 10 million (approximately 12%) of the German population were born outside of Germany, mostly from Turkey, Russia, Poland and Italy.60 Italian and Polish groups are responsible for a third of German offences committed by EU FNO. It is estimated that the high volume of Italian and Polish nationals residing in Germany assist the Italian and Polish crime groups in becoming leading figures within the German drugs market.
60 http://worldpopulationreview.com/countries/germany-population/
acro.police.uk 67 18.11 Italian nationals are involved in drug crimes more often than any other EU FNO. This may be related to Italian mafia group known as ‘Ndrangheta which are reported to have a strong presence in the German drug market. In Europol’s threat assessment, mafia-style Italian organised crime is recognised as a clear and present threat to Europe.61 The ubiquity of ‘Ndrangheta networks across Europe, strong family ties, and reluctance to collaborate with law enforcement enable the ‘Ndrangheta to retain an important role in the Italian and German distribution of cocaine62 (Europol, 2013).
18.12 The third highest offending nationality in Germany after the Italians and Polish are the Dutch. This may be related to the drug route to which drugs enter Europe via Rotterdam seaport in the Netherlands. Once it is imported in to the Netherlands, it is inferred that Dutch OCGs move the drug to other consumer markets, particularly the neighbouring countries such as Germany which could account for the high proportion of Dutch nationals in Germany.
18.13 Analysis identified how the top three nationalities (Italian, Polish and Dutch) are disproportionately linked to either the possession or trafficking of drugs. For example, Italian and Polish nationals are predominantly linked to the possession of drugs offences, whereas the Dutch are more often linked to drugs trafficking which ties in with the Netherlands being recognised as a key source countries for drug reception within the EU.
18.14 Analysis of the cocaine and heroin related offences identified the majority of cases are dealt with in Frankfurt (figure 18.3). The dataset shows that 134 cocaine, 64 heroin and two convictions relating to both drug types have been trialled at Frankfurt. Munich follows in second place with nine cocaine cases, 19 heroin and two relating to both cocaine and heroin.
18.15 It could be inferred that the disproportionate amount of occurrences at Frankfurt is due to Frankfurt Main Airport. The airport is the third largest in Europe (eleventh worldwide) in terms of passenger numbers (59.6 million a year) and the largest in Europe (top ten worldwide) in terms of cargo (two million tonnes a year).63 The large amount of people and cargo at Frankfurt Main supports the disproportionate amount of drug offences occurring in the city suggesting the airport may be an air trafficking hub for drugs into Europe. In support of this, it is reported that the majority of cocaine is trafficked from South America via air mail or air courier services through Frankfurt Main airport.64
61 Europol Threat Assessment, Italian Organised Crime (2013) 62 www.ocportfolio.eu/_File%20originali/OCP%20Full%20Report.pdf 63 Fraport, “2015 Facts and Figures on Frankfurt Airport”, available at: http://www.fraport.com/content/fraport/en/misc/binaer/press-center publications/2015/2015-facts-and-figures-on-frankfurt-airport/jcr:content.file/facts-and-figures_2015.pdf 64 Drug dealer’ careers, behaviours and strategies – in their own words. A study of imprisoned drug dealers in Italy, Slovenia and Germany (2014). Available at; https://www.researchgate.net/publication/279846112_Drug_dealers’_careers_behaviours_and_strategies_-_in_their_own_words_A_study_of_imprisoned_ drug_dealers_in_Italy_Slovenia_and_Germany_ALICE-RAP_Addiction_Revenues_WP_10
68 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 18.3 - Hotspot map for FNO drug offences in Germany by drug type65
18.16 The Frankfurt anomaly is reduced upon analysis of all 16,755 drug offences when measured against the court location. Reviewing the court location of all drug types reveals a concentration of offences in Munich with 1,207 offences, followed by Düsseldorf with 459 offences.
18.17 Of interest, in third place a large number (411) of offences were reported to have been heard at court in Nordhorn (figure 18.4), a small western town bordering the Netherlands with a population of 53,285.66 To put this in perspective, a similar number of offences (459) were reported in Dusseldorf, a larger city with a population of 612,178,67 over ten times the size of Nordhorn.
65 Geographically mapped using court location 66 https://www.quandl.com/data/CITYPOP/CITY_NORDHORNNIGERMANY-Population-of-Nordhorn-NI-Germany 67 http://www.citypopulation.de/php/germany-nordrheinwestfalen.php?cityid=05111000
acro.police.uk 69 Figure 18.4 - Top 5 court locations for drugs offences in Germany committed by FNO
18.18 Germany shares a border with nine other countries, Denmark in the north, Poland and the Czech Republic in the east, Switzerland and Austria in the south, France in the southwest and Belgium, Luxembourg and the Netherlands in the west. A high proportion (42.40%) of German offences are committed by FNOs from these neighbouring countries, particularly the Polish, Dutch, French, Austrian and Czechs.
18.19 Further geographical analysis identified FNO offences are largely prevalent in the regions along the German-Dutch border, particularly in areas such as Aachen, Kleve and Emmerich (figure 18.5). Dutch nationals occupy a significant role in the trafficking or importing of drugs, especially in these border towns. For example, a high proportion of trafficking offences were reported in both Aachen and Kleve, being 47.47% and 75.20% respectively and in Emmerich, 75% related to the importation of drugs. It can be inferred that the liberal drug policy (in relation to cannabis) of the Dutch authorities has led to an increased level of offending at this border.
70 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 18.5 - Map of court location for drug offences in Germany committed by FNO68
18.20 Males are predominant in drugs related offences accounting for 90.58% (15,176 of the 16,755) of the total offence count with 1,577 offences being committed by women.
18.21 Analysis of the 16,755 offences identified the average age of an offender at the time of conviction is 32. This rises to 37.9 years of age for those offenders convicted of cocaine related offences in comparison to 38.3 for heroin offences. A comparison between gender groups shows the average age of offenders to be similar between men (32.2 years) and women (31.7 years).
18.22 This next section is based on conviction information received by Germany from a MS referring to convictions of a German national in their country.
68 Mapped those courts with a count greater than or equal to 150 cases
acro.police.uk 71 18.23 The German CA identified those offences that were committed by German nationals outside of their home country. A total of 2,575 were reported to have a final conviction date between 2013 and 2014.
Figure 18.6 - Top ten EU countries with the highest German offending rates (2013 - 2014)
Nationality German FNO Percentage
Spain 803 31.18% Poland 734 28.50% Italy 295 11.46% Austria 258 10.02% France 139 5.40% Netherlands 104 4.04% Belgium 84 3.26% UK 64 2.49% Czech Republic 18 0.70% Denmark 14 0.54%
72 Criminal record analysis to support the European Pact on International Drug Trafficking 19 Belgium
19.1 Belgium provided the project team with the following data:
Data Source Date Parameters
National System 2013 - 2014
19.2 Due to legislative constraints, Belgium CA were unable to distinguish between drug type and separate offences between cultivation, possession and supply type offences. As a result the subsequent analysis is based on a variety of drugs.
19.3 Belgium started to exchange conviction information utilising ECRIS in July 2012. Initially Belgium was connected to two other countries; the UK and the Netherlands, increasing to 18 countries in 2013. At the time of writing this report, Belgium is connected to 23 other MS.69
19.4 Seizure statistics for Belgium identify that cocaine is the main illicit Class A drug seized. In 2011, approximately 7,999kg of cocaine was seized which more than doubled to 19,177kg in 2012 decreasing again in 2013 to 6,486kg to 9,293kg in 2014. Whereas, heroin seizures remained steady in 2011 (140kg) and 2012 (112kg) but increased ten-fold to 1,182kg in 2013 decreasing again in 2014 to 140kg.
19.5 Belgium is not known as a drug producing country but it remains an important transit country for illicit drugs bound for the Netherlands, UK and other areas in Western Europe. EMCDDA recognises that Belgium and the Netherlands are the most important entry points for South American cocaine reaching the European market, largely due to both these countries hosting two major seaports within the northern region of Europe, Rotterdam and Antwerp.70 It is understood that drugs enter Belgium either by shipping containers moving drugs through the port of Antwerp or it is carried by drug couriers flying into the country or imported through the border of Belgium’s neighbouring countries.
19.6 Between 2013 and 2014, in Belgium, 18,198 drugs offences were committed by Belgian nationals and FNO. A wide range of criminal offenders participate in Belgium’s illicit drugs market. Between 2013 and 2014, over 65 different nationalities were convicted in Belgium for drug related offences. As highlighted in figure 19.1, Belgian nationals account for 69.64% of the total offence count, with offences evenly split between foreign EU (12.47%) and Non EU offenders (14.33%), and the remaining 3.56% where nationality was unknown.
69 Belgium is currently not exchanging with Greece, Malta, Portugal or Slovenia 70 http://www.emcdda.europa.eu/system/files/publications/2374/TD0416161ENN_1.PDF
acro.police.uk 73 Figure 19.1 - National offence data for Belgium (2013 - 2014)
Total Belgian EU FNO Non EU FNO Unknown
Offences 18,198 12,673 2,270 2,607 648
% 100% 69.64% 12.47% 14.33% 3.56%
19.7 After removing Belgian nationals from the dataset, 5,525 offences remained. Unless stated otherwise all Belgian nationals have been excluded from the subsequent analyses.
Figure 19.2 - Top ten FNO Nationalities involved in drugs offences in Belgium (2013 - 2014)
Nationality Number Percentage
Morocco 1,151 20.83% Netherlands 1,008 18.24% Unknown 648 11.73% France 515 9.32% Algeria 502 9.09% Italy 183 3.31% Turkey 143 2.59% Tunisia 122 2.21% Spain 94 1.70% Poland 90 1.63%
19.8 Moroccans were responsible for the largest proportion of drugs offences between 2013 and 2014, accounting for 20.83% of the total foreign offence count, followed by the Dutch nationals with 18.24%. The high proportion for Moroccans and Dutch suggests that both Morocco and The Netherlands are pivotal as production and transfer points for Europe-bound drug flows.
19.9 Five of the ‘top ten’ offending nationalities in figure 20.2 (Moroccans, French, Italian, Dutch and Polish) feature in the top five foreign born populations in Belgium (see figure 19.3) suggesting a possible correlation between the size of foreign national communities in Belgium and the volume of offending that may be attributable to them.
74 Criminal record analysis to support the European Pact on International Drug Trafficking 19.10
Figure 19.3 - Population of Belgian and foreign nationals residing in Belgium71
Citizenship Total
Total 11,267,910 Belgian Nationals 10,210,244 Foreign Nationals 1,057,666 French 159,352 Italian 156,977 Dutch 149,199 Moroccan 82,009 Polish 68,403
19.11 Geographical analysis identified Antwerp, Charleroi, Brussels and Ghent as hotspots for drugs related Nationality Number Percentage offences. As already noted, Antwerp in Belgium is recognised as one of the main seaports (as well
Morocco 1,151 20.83% as Rotterdam in the Netherlands) for importing cocaine into Europe, which may imply why a large Netherlands 1,008 18.24% number (20.20%) of drugs offences occur in this region. In support of this, EMCDDA recognise Unknown 648 11.73% Belgium as playing a major role in the trafficking of drugs largely due to its central geographic location France 515 9.32% within Europe combined with its easy access points, such as the large port of Antwerp.72 It is reported Algeria 502 9.09% that this port is attractive to drugs traffickers as only 2% of the 8 million containers are screened.73 Italy 183 3.31% Turkey 143 2.59% However, it is important to note that the disproportionate number of offences in this region could be Tunisia 122 2.21% due to Antwerp having the largest geographical remit within the dataset. Spain 94 1.70% Poland 90 1.63% 19.12 Charleroi, near Brussels has the second highest offence count in Belgium after Antwerp. A contributing factor to the high offence rate in this area could be the high unemployment rates of 25.09%74 (August 2015), a rate that was well above the national average of 8.03%75 (January 2016).
19.13 Brussels is the third largest hotspot for drug related crime. Brussels is the capital of Belgium and holds the largest metro population (1,789,447)76 which could account for the higher incidence of drug crime. Brussels also hosts an international airport, which EMCDDA report as ‘pivotal’ to international drugs trafficking.77 Additional rail links connect Brussels to the UK, The Netherlands, Germany, France, Luxembourg and Paris making city internationally accessible to transport drugs for onward distribution throughout Europe.
71 Portal Belgium (2015) - http://www.belgium.be/en/about_belgium/country/Population/ 72 http://www.emcdda.europa.eu/system/files/publications/1004/BAR2014%20Final%20EMCDDA%20Version.pdf 73 https://www.theguardian.com/world/2014/jun/01/antwerp-belgium-cocaine-capital-drugs-trade-pigeons 74 Financial Times, available at: https://www.ft.com/content/c44a4918-7349-11e5-bdb1-e6e4767162cc 75 http://www.tradingeconomics.com/belgium/unemployment-rate 76 http://www.worldatlas.com/articles/biggest-cities-in-belgium.html 77 http://www.emcdda.europa.eu/countries/belgium
acro.police.uk 75 19.14 Belgium shares a border with four countries, the Netherlands, France, Germany and Luxembourg. Analysis identified that the Dutch, French, German and nationals from Luxembourg are engaged in cross-border activity within Belgium. The following map demonstrates that there is limited geographical movement from the offender’s home country to where the subject was convicted suggesting cross border drugs activity. For example, a large proportion of Dutch nationals were convicted near the Dutch-Belgian border, suggesting a possible collaboration between crime groups from both countries. This trend is reflected with each of the neighbouring countries suggesting that exchanges of drugs and cash may be made more frequently close to borders as drug couriers minimise the amount of travel to reduce costs and risk of detection as these typically increase as more territory and international borders are traversed.
Figure 19.4 - Map of cross-border drugs activity in Belgium
76 Criminal record analysis to support the European Pact on International Drug Trafficking 19.15 The data indicated that the majority (94.03%) of offences were committed by men and were aged between 20 and 39.
Notifications In
19.16 This next section is based on conviction information received by Belgium from a MS referring to convictions of a Belgian national in another MS.
19.17 The Belgium CA identified those offences that were committed by Belgian nationals outside of their home country. A total 471 offences were reported to have a conviction dated between 2013 and 2014.
19.18 Belgian nationals appear to be most active in the four neighbouring countries, France, The Netherlands, Luxembourg and Germany.
Figure 19.5 - Top ten EU countries with the highest Belgian national offending rates (2013 - 2014)
Nationality Total Percentage
France 233 51.32% Netherlands 67 14.76% Luxembourg 34 7.49% Germany 26 5.73% United Kingdom 25 5.51% Spain 23 5.07% Hungary 13 2.86% Italy 11 2.42% Denmark 5 1.10% R.O.I 4 0.88%
acro.police.uk 77 20 Hungary
20.1 Hungary provided the project team with the following data:
Data Source Type Date Parameters
ECRIS NO 2013 - 2014
20.2 The Hungarian CA provided the offence location enabling the project team to geographically map the data. However, Hungarian legislation does not allow separate classification of offences by drug type nor are they able to differentiate between the supply, possession or manufacturing of drugs.
20.3 Hungary CA provided the project team with ECRIS NO data. It is important to note that Hungary initially started exchanging ECRIS data with Austria in October 2012, but did not start exchanging with other countries until February 2013. Therefore the dataset is comparatively smaller than the other datasets the project team have processed. For example, Hungary sent five notifications in 2013 and 48 in 2014.
20.4 Hungary has been identified as a transit country for drugs from Turkey and Asia to Europe. UNODC report that “most cocaine shipments appear to travel from Greece, either through Bulgaria, Romania and Hungary and further into Western and Central Europe.” 78
20.5 The Hungarian drug market experienced a ‘heroin shortage’ between 2011 and 2013 which is indicated by the low seizure data.79 Compared to 2010 (97.79kg) relatively small amounts of heroin were seized in 2011 (3.17kg), 2012 (2.52kg) and 2013 (5.72kg) increasing in 2014 to 70.06kg. Both Poland and Czech Republic follow a similar trend in the seizure data but the extent of the shortage in other European countries is less clear. Cocaine seizures increased from 12.55kg in 2011 to 13.31kg in 2012, decreasing to 8.13kg in 2013 before increasing to a record high over the four years of 39.65kg.
Figure 20.1 - Top ten NO countries (2013 - 2014)
Country Number Percentage
Austria 22 41.51% France 8 15.09% Belgium 7 13.21% Bulgaria 5 9.43% Germany 3 5.66% Czech Republic 3 5.66% Poland 2 3.77% R.O.I 1 1.89% Sweden 1 1.89% UK 1 1.89%
78 https://www.unodc.org/documents/data-and-analysis/Studies/Illicit_DT_through_SEE_REPORT_2014_web.pdf 79 http://www.emcdda.europa.eu/countries/hungary
78 Criminal record analysis to support the European Pact on International Drug Trafficking 20.6 Geographical mapping analysis identified that cross border activity is evident as many of the offences occur in towns that are situated on the border of Hungary. More specifically, the town of Rajka has the highest frequency of offences (33.96%). Interestingly this small town (with a population of approximately 2,700) sits on the border of Hungary, Austria and Slovakia and therefore it can be inferred that the town is strategically placed to transport illegal drugs internationally. However, the project team acknowledge this could just be the result of having such a small dataset.
20.7 The majority of notifications (77.36%) relate to the common category ‘manufacture or production of narcotics’. The category which relates to the illicit trafficking of narcotics accounts for just 7.5% (four notifications in total) although it should be noted that analysis of this information is limited as each MS classify their drugs offences differently.
20.8 In terms of gender; the male population account for the majority of offences (86.79%).
Country Number Percentage
Austria 22 41.51% France 8 15.09% Belgium 7 13.21% Bulgaria 5 9.43% Germany 3 5.66% Czech Republic 3 5.66% Poland 2 3.77% R.O.I 1 1.89% Sweden 1 1.89% UK 1 1.89%
acro.police.uk 79 21 Croatia
21.1 Croatia provided the project team with the following data:
Data Source Type Date Parameters
ECRIS NO 2013 - 2015
ECRIS NI 2013 - 2015
National system 2011 - 2015
21.2 Croatia were unable to provide offence location or drug type and so the project team were unable to geographically map offence location or provide any further analysis of drug type trends.
21.3 In relation to ECRIS data, Croatia were not able to fulfil the project date parameters (2013 and 2014) as Croatia only became operational on ECRIS in July 2013, the month in which they joined the EU. For this reason, much of the analysis is based on the national data provided by the Croatian CA.
21.4 EMCDDA identify a downward trend of heroin seizures between 2011 (33.1kg) to 2013 (10.43kg) but increased in 2014 to 46.85kg. Whereas, cocaine seizures followed an upward trend from 2011 to 2013 from 4.07kg to 9.10kg but decreased in 2014 to 5.84kg.80 The seizure statistics indicate that out of both heroin and cocaine, heroin is the main illicit drug seized in Croatia.
21.5 By Croatia joining the EU it opened a 1,377km-long border between the Western Balkans and the EU81 making it an attractive country to be exploited by drugs traffickers. Due to its geographical positioning in Europe and as part of the Balkan route, Croatia remains a transit country for heroin being trafficked between production countries such as Afghanistan and consumption countries in Western Europe.82 The Balkan route is also reportedly used for trafficking cocaine from South America.83 The INCSR states that most “illicit drugs smuggled into Croatia are bound for consumer markets in Europe and elsewhere, though a small percentage is consumed locally.” 84
80 http://www.emcdda.europa.eu/countries/croatia 81 https://www.unodc.org/documents/data-and-analysis/Studies/Illicit_DT_through_SEE_REPORT_2014_web.pdf 82 http://www.state.gov/j/inl/rls/nrcrpt/2013/vol1/204049.htm 83 https://www.export.gov/article?id=Croatia-Safety-and-Security 84 http://www.state.gov/j/inl/rls/nrcrpt/2013/vol1/204049.htm
80 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 21.1 - National offence data for Croatia (2011 - 2014)
Total Croatian EU FNO Non EU FNO Unknown
Offences 6,373 5,026 352 991 4
Percentage 100% 78.86% 5.52% 15.55% 0.07%
21.6 Croatian nationals accounted for 78.86% of the total offence count, whereas, the number of foreign citizens reported for drugs offences account for 21.07%, with 5.52% relating to EU FNO, 15.55% for Non EU FNO and the remaining 0.07% unknown. The following analysis is based on both Croatian nationals and FNO unless specified otherwise.
21.7 Analysis of the Croatian data identifies a year on year decrease in the number of drugs offences in Croatia (figure 21.2). Overall, there has been a 62.45% decrease from 2011 (2,469) to 2014 (927). It is clear that although there is a decline in offences from 2013 to 2015, it isn’t as significant as the decline from 2011 to 2013. This is largely accountable to the new amendment in the criminal code that came into effect in 2013, whereby possession of small quantities of drugs for personal use is no longer dealt with as a criminal offence but instead it was classed as a misdemeanour, usually punishable by a fine.85
21.8
Figure 21.2 - Number of offences in Croatia (2011-2014)
2500
2000 ces n e ff o f 1500 o r be m Nu
1000
500
1 2 3 4 1 1 1 1 0 0 0 0 2 2 2 2 Year
21.9 From 2011 to 2014, over 35 different nationalities were convicted in Croatia. Bosnian and Herzegovinian nationals are involved in drugs crime more often, followed by Serbians, Macedonians, Germans and Slovenians.
85 http://www.emcdda.europa.eu/countries/croatia
acro.police.uk 81 Figure 21.3 - Top ten FNO involved in drug offences in Croatia (2011-2014)
Country of Nationality Number Percentage Bosnia and 565 41.95% Herzegovina Serbia 185 13.73% Macedonia 119 8.83% Germany 111 8.24% Slovenia 103 7.65% Kosovo 36 2.67% Albania 31 2.30% France 26 1.93% Austria 22 1.63% Montenegro 20 1.48%
21.10 As previously mentioned, analysis identifies a prominent involvement of Bosnian and Herzegovinian nationals (see figure 21.3) in the Croatian drugs market. It can be inferred that these nationals are heavily involved as their home country borders Croatia, sharing a long border of 931km86 making the country more vulnerable to cross border trafficking or it may be related to already established drug supply routes as Croatia sits on the ‘central branch’ of the Balkan route in which EMCDDA report is a common heroin trafficking route from Afghanistan through to Bosnia and Herzegovina before entering Croatia in Eastern Europe for onward distribution to the ‘high value’ Western European markets.87
21.11 According to the 2011 census, Serbs were the largest populous group in Croatia, constituting 4.40% (189,200) of the total population whereas, only 0.70% (30,100)88 are from Bosnia and Herzegovina89 (figure 21.4). However, Bosnia and Herzegovina nationals had the highest drug offending prevalence rate (41.95%), followed by Serbian nationals in second place with 13.73%.
86 http://www.visitmycountry.net/bosnia_herzegovina/en/index.php/geography/27-vmc/geografija/226-the-borders-and-size-of-bosnia-and-herzegovina 87 http://www.emcdda.europa.eu/system/files/publications/2373/TD0216072ENN.PDF 88 http://www.croatia.eu/article.php?lang=2&id=15 89 http://www.croatia.eu/article.php?lang=2&id=15
82 Criminal record analysis to support the European Pact on International Drug Trafficking Figure 21.4 - Number of Croatian and FNO nationals residing in Croatia in 201590
Citizenship Total Percentage Country of Nationality Number Percentage Total Croatian 4,300,000 100% Bosnia and Population 565 41.95% Herzegovina Croatian Nationals 3,887,200 90.40% Serbia 185 13.73% Foreign Nationals 412,800 9.60% Macedonia 119 8.83% Serbian 189,200 4.40% Germany 111 8.24% Bosnian 30,100 0.70% Slovenia 103 7.65% Albanian 17,200 0.40% Kosovo 36 2.67% Italian 17,200 0.40% Albania 31 2.30% Romanian 17,200 0.40% France 26 1.93% Hungarian 12,900 0.30% Austria 22 1.63% Slovenian 12,900 0.30% Montenegro 20 1.48% Macedonian 4,300 0.10% Montenegrin 4,300 0.10% Slovakian 4,300 0.10% Other 103,200 2.40%
21.12 In 2011 and 2012 a large majority of convictions related to the possession of drugs. While the rates of possession offences declined substantially in 2013 through to 2015, trafficking offences increased (see figure 21.5). These changes can be largely accountable to the amendment in the Croatian penal code in 2013. This amendment enabled Croatian authorities to distinguish between the possession of drugs for personal consumption (treated as a misdemeanour offence) from those that possess drugs with an intention of putting them into circulation, as a consequence the number of trafficking offences recorded in Croatia increased.
21.13 Figure 21.5 - Number of Trafficking and Possession offences in Croatia
2500
2000
1500
1000
500
0 2011 2012 2013 2014
Trafficking Possession
90 http://www.croatia.eu/article.php?lang=2&id=15
acro.police.uk 83 21.14 In terms of gender, males have a higher prevalence rate for drug offences in Croatia. Overall, the majority of offences (88.50%) related to males, 7.39% females and the remaining 4.11% were unknown.
21.15 The peak age range for those convicted of drugs offences in Croatia are persons aged between 20 - 39 years of age.
ECRIS Notifications Out
21.16 At the time of writing this report, Croatia was exchanging ECRIS data with 13 other MS (see Appendix A). In 2013, Croatia started exchanging with Austria, Czech Republic and Spain and increased to exchanging with eight further countries in 2014 and two further countries in 2015.
21.17 There was insufficient data (four notifications) to enable the project team to analyse the NO data.
ECRIS Notifications In
21.18 The ECRIS NI analysis is based on notifications received by Croatia from MS referring to conviction information of Croatian nationals in another MS. This section provides data and analysis for those notifications with a final conviction in either 2013 or 2014 relating to the five ECRIS common categories.
21.19 Croatia received 155 notifications relating to drugs convictions between 2013 and 2015 from eight different MS91 predominantly from Germany (51.61%) followed by Italy (15.48%), Austria (14.19%) and the UK (10.32%). The number of notifications received increased year on year for two reasons. Firstly, the number of countries Croatia started exchanging with increased from three MS in 2013 to 10 MS in 2015. Secondly, only six months of data was captured in 2013 as Croatia only started exchanging data mid-2013.
Figure 21.6 - Top notifying countries
Notifying country Total Percentage
Germany 80 51.61% Italy 24 15.48% Austria 22 14.19% UK 16 10.32% France 7 4.52% Spain 4 2.58% Sweden 1 0.65% Poland 1 0.65%
91 Croatia have received notifications from Germany, Poland, Sweden, Italy, United Kingdom, France, Austria and Spain
84 Criminal record analysis to support the European Pact on International Drug Trafficking 21.21 The large majority of notifications received by MS relate to the ECRIS common category; “offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors not exclusively for own personal consumption”, suggesting that a large majority of Croatian nationals are convicted in Europe for trafficking offences. However, it is important to note that analysis of ECRIS common categories is limited as each MS will classify drugs offences differently.
Figure 21.7 - NI received by Croatia by common category
Common category Number
Offences related to illicit trafficking in narcotic drugs, psychotropic substances and precursors not 90 exclusively for own personal consumption
Offences related to drugs or precursors, and other offences against public health 27
Illicit consumption of drugs and their acquisition, possession, manufacture or production exclusively for 24 own personal consumption
Manufacture or production of narcotic drugs not exclusively for personal consumption 11
Aiding or inciting others to use narcotic drugs or psychotropic substances illicitly 3
21.22 Of those Croatian nationals convicted throughout Europe, the large majority are male between the ages of 20 – 39.
21.23 Croatia has not received any notifications from certain countries despite those countries being connected through ECRIS. The following countries concerned are; Belgium, Czech Republic, Finland, R.O.I, The Netherlands, Poland and Sweden, suggesting Croatian nationals are not particularly active in relation to drugs trafficking in these countries.
21.24 Further analysis identifies that in Germany, Croatian nationals were linked to trafficking of drugs offences rather than possession or supply of drugs offences. Whereas, in Italy, Croatian nationals are largely linked to drugs use/possession offences. A possible factor in this may be the manner in which offences are recorded in the respective countries.
acro.police.uk 85 22 Italy
22.1 Italy provided the project team with the following data:
Data Source Type Date Parameters
ECRIS NO 2013 - 2014
ECRIS NI 2013 - 2014
22.2 The analysis in this section relate to those Italian notifications (NO) that fall under one of the five common ECRIS categories that were concluded in 2013 or 2014.
22.3 Due to legislative constraints, Italy are unable to distinguish the drug type or category of offence, for example, cultivation, possession and supply. Therefore, the analysis on the Italian data is not limited to cocaine, crack cocaine or heroin and instead relates to all drugs offences.
22.4 In 2013, Italy became operational on ECRIS and was initially exchanging conviction data with 16 other MS. At the time of writing this report, Italy was exchanging ECRIS data with 22 other MS (Appendix A).
22.5 In relation to Italian drug seizures, cocaine is reported to be the main illicit Class A drug seized in the country followed by heroin. EMCDDA report that the Italian authorities seized a record amount of cocaine (6,344kg) in 2011, declining year on year from 2012 (5,300kg) to 2014 (3,866kg). Whereas, heroin seizures fluctuated between 813kg and 931kg between the period of 2011 and 2014.
22.6 EMCDDA report that Italy is an important transit country and consumer of illicit drugs.92 Research showed that both heroin and cocaine are imported, heroin is shipped to Italy mainly along the Balkan route originating from Afghanistan, while cocaine originating mainly from South America, in particular Colombia enters Italy through the countries numerous seaports.93
22.7 The project team received an ECRIS NO dataset containing 5,838 rows of data. Quality assurance checks identified that the 5,838 rows of data did not reflect 5,838 unique offences. The project team removed offences that were duplicated,94 offences that were either deemed not relevant to the project (e.g. medicinal offences or doping) and/or the final conviction date sat outside the project date parameters (2013 - 2014). This process reduced the data from 5,838 to 467 rows of data.
92 http://www.emcdda.europa.eu/countries/italy 93 http://www.state.gov/j/inl/rls/nrcrpt/2016/vol1/253276.htm 94 Removed offences that were duplicated as a result of one offence receiving multiple sanctions
86 Criminal record analysis to support the European Pact on International Drug Trafficking 22.8 Italy sent 467 offence notifications with a final conviction date between 2013 or 2014. The top ten countries accounted for 96.57% of the total offence count with the majority being sent to Romania, Germany and France (68.31%)
Figure 22.1 - Top ten NO countries by nationality
Country of Nationality Number Percentage Romania 191 40.90% Germany 66 14.13% France 62 13.28% Spain 41 8.78% Poland 32 6.85% Bulgaria 31 6.64% Belgium 10 2.14% Czech Republic 6 1.28% UK 6 1.28% Austria 6 1.28%
22.9 The large majority of notification offences relate to males (81.37%) between the ages of 20 – 39.
ECRIS Notifications In
22.10 The project team received the NI data from the Italian CA, however the quality assurance method adopted by the project team highlighted a number of notifications were missing from the Italian NI dataset therefore the project team have opted not to process this data.
acro.police.uk 87 23 Key findings
Overall Findings
23.1 National drug laws provide significant variations in the way offences are classified, as well as the extent to which convictions are recorded across EU MS. For example, the number of offence types recorded by the co-beneficiaries is significantly fewer in comparison to the number of offence types recorded in the UK as other MS do not distinguish between the criminal use and/or drug type. Consequently, the ability to differentiate between drug type, possession, supply or distribution of a drug across MS is difficult.
23.2 The continued importance of the Balkan route for heroin trafficking is evident in large seizures at key stages of the route, for example in 2014, Turkey, Italy and Greece seized higher quantities of heroin than any other European country.
23.3 The presence of foreign nationals are closely related to key entry points into Europe. There is a much larger number of Carribean nationals, particularly Jamaicans and Dominicans that are convicted for drugs offences in the UK, whereas, Moroccans play a leading role in both Spain and Belgium. However, it appears in Lithuania and Romania that the domestic drugs market is largely in the hands of their own nationals with little influence from foreign national offenders.
23.4 The territorial distribution of drug convictions across the participating MS identified the highest number of offences were made in regions with the largest urban centres, for example, Madrid, London and Vilnius. This is likely due to an increased availability of drugs in these areas which is assisted by larger volumes of people living in the area and subsequently more drugs users, increased tourism as well as improved air and maritime links.
23.5 Geographical analysis identified offences committed by FNO are also largely prevalent along country borders. This is evident in Belgium, Germany and Hungary suggesting a possible collaboration between crime groups between the neighbouring countries. In general, the participation of these countries in the Schengen open border system contributes to its desirability as a transit point for drugs.
23.6 Within Europe, some specific geographical locations known as ‘hotspots’, remain particularly important for drug production or trafficking. Some of these areas are long established, such as Antwerp in Belgium and Andalucía in Spain, while some locations appear to be emerging such as Nordhorn in Germany and Rajka in Hungary.
23.7 There is an apparent correlation between the size of foreign communities and the volume of offending that may be attributable to them. For example, Poland has the largest community in England and Wales coupled with the highest FNO offence rate. Similarly, people from Non EU countries that have historical and linguistic ties to an EU country appear to be associated with drug trafficking, for example, there is a
88 Criminal record analysis to support the European Pact on International Drug Trafficking large number of Colombian nationals convicted for drugs offences in Spain and a contributing factor of this is that there is no language barrier between the two countries.
UK key findings
23.8 Cocaine is the drug most often associated with offences for which foreign nationals are convicted in England and Wales with cocaine accounting for 45.35% of the total FNO offence count, followed by heroin (35.19%), and crack cocaine (19.46%).
23.9 Analysis of the PNC data identified Jamaica, Somalia and Poland as the top three foreign offending nationalities. Jamaican nationals appear to dominate the UK drug market across all three drug types, with the majority of offences relating to the supply of drugs. This over representation could be linked to already established drug supply routes as the Caribbean is understood to act as a primary transit point for the trafficking of cocaine destined for the UK.95
23.10 Of interest, Portuguese nationals feature highly in the UK data. It is possible that those FNO recorded as Portuguese may in fact be from India as there is a provision in Portuguese nationality law that enables Indian nationals to become EU residents if they were born before 1961 in areas which were once Portuguese colonies such as, Goa, Daman and Diu. It is inferred that heroin is being trafficked into the UK via Portugal by Indian-born Portuguese nationals as their home country of India is known to be used as a hub for the transhipment of heroin originating from Afghanistan.
23.11 ECRIS data identifies that Dutch nationals are high in their involvement of the supply of drugs as opposed to the possession or manufacture of drugs. It is inferred that The Netherlands is a key country involved in the receipt and onward movement of drugs to the UK.
23.12 Analysis of the nationality of offenders within the UK highlights the international diversity of drugs offenders. With over 190 different nationalities being convicted between 2011 and 2014.
Spain key findings
23.13 From the available data supplied, Spain has the largest proportion of FNO than any other MS participating in the project. FNO accounted for 43.54% of the total offence count which were committed by over 140 different nationalities.
23.14 In Spain, analysis identified Morocco and Colombia as the nationalities of interest, together with Romania and Portugal for the EU countries. Moroccan and Colombian nationals have a high incidence in the commission of drugs offences in Spain as both countries are linked to already established drug production and supply routes.
95 Immigration Enforcement Threat Assessment, Immigration Intelligence, May 2014
acro.police.uk 89 23.15 The greatest percentage of drugs convictions occur in Madrid, followed by Ceuta, Barcelona and Algeciras.
23.16 Latin American countries are heavily represented in relation to female offending in Spain whereas, for those offences committed by male offenders a high proportion are of Moroccan and Colombian nationality.
Lithuania key findings
23.17 Analysis identified a very small number of FNO committing cocaine and heroin related offences over the four years.
23.18 A high proportion of Lithuanian offences are linked to heroin in comparison to cocaine indicating that Lithuania is used as a transit country for trafficking heroin to other countries.
23.19 Geographical analyses identified that Vilnius followed by Klaipeda and Kaunas are hotspots for both cocaine and heroin offences.
23.20 Approximately a third of all Lithuanian offences occurred in a territory of Vilnius, specifically linked to a Roma village of the Kirtimai Tabor community. It is inferred that social exclusion from the labour market may push the Roma community towards drug trafficking as a principle source of income.
Romania key findings
23.21 Analysis identified a very small number of EU FNO committing drug related offences with 140 FNO reported to have committed drugs offences over the four years.
23.22 Analysis of the Romanian data identified Turkey, Moldova and Italy to be the top three offending nationalities.
Germany key findings
23.23 Italian and Polish groups are responsible for approximately a third of German offences committed by EU FNO. It is assumed that the high volume of Italian and Polish nationals residing in Germany assist the Italian and Polish crime groups in becoming lead figures within the German drugs market. The mafia-style Italian OCG known as ‘Ndrangheta presents a clear threat to Germany, as they retain an important role in the German distribution of cocaine.
90 Criminal record analysis to support the European Pact on International Drug Trafficking 23.24 Analysis identified Munich, Dusseldorf and Nordhorn as hotspots for drugs related offences. Interestingly, Nordhorn (placed third) is a small western town bordering the Netherlands. To put this in perspective, a similar number of offences were reported in Dusseldorf, a larger city with over ten times the population of Nordhorn. It can be inferred that Nordhorn is being used as a trafficking hub for drugs entering the country.
23.25 Analysis identified how the top three nationalities (Italian, Polish and Dutch) are disproportionately linked to either the possession or trafficking of drugs. For example, Italian and Polish nationals are predominantly linked to the possession of drugs offences, whereas the Dutch are more often linked to drugs trafficking which ties in with The Netherlands being recognised as a key source countries for drug reception within the EU.
23.26 FNO offences are largely prevalent in the regions along the German-Dutch border, particularly in areas such as Aachen, Kleve and Emmerich. Dutch nationals occupy a significant role in the trafficking and importing of drugs, especially in these border towns.
Belgium key findings
23.27 Moroccans and Dutch were identified as being heavily involved in the Belgian drugs market, suggesting that both Morocco and The Netherlands are pivotal as production and transfer points for Europe-bound drug flows transitting Belgium.
23.28 Analysis identified that a large proportion of drug offences occur in Antwerp. It is inferred that this is due to its status as a transit country, its central position in Europe and Antwerp’s position as a major port.
23.29 Analysis identified that nationals from The Netherlands, France, Germany and Luxembourg are engaged in cross-border activity within Belgium. This suggests that exchanges of drugs and cash may be made more frequently close to borders as drug couriers minimise the amount of travel to reduce costs and risk of detection as these typically increase as more territory and international borders are traversed.
Hungary key findings
23.30 Geographical mapping analysis identified that cross border activity is evident as many of the offences occur in towns that are situated on the border of Hungary. More specifically, the town of Rajka has the highest frequency of offences (33.96%). Interestingly this small town (with a population of approximately 2,700) sits on the border of Hungary, Austria and Slovakia and therefore it can be inferred that the town is strategically placed to transport illegal drugs internationally. However, the project team acknowledge this could just be the result of having such a small dataset.
acro.police.uk 91 Croatia key findings
23.31 The criminal code that came into effect in 2013 altering the way in which possession offences are dealt with resulted in a significant decrease in the number of drugs offences from 2013 to 2014.
23.32 There is a prominent involvement of Bosnian and Herzegovina nationals in the Croatian drugs market. It can be inferred that the long border between these two countries makes Croatia more vulnerable to cross border trafficking. Serbians and Macedonians are placed second and third respectively.
Italy key findings
23.33 In relation to ECRIS notifications out, Romania, Germany and France were found to be high in comparison to any other country, accounting for 68.31% of the total notification count.
92 Criminal record analysis to support the European Pact on International Drug Trafficking 24 Conference
24.1 Work stream three relates to the organisation and hosting of an international conference to present the project findings to partners and stakeholders.
24.2 There are five key stages to work stream three:
1. Research/requirements 2. Procurement 3. Delegate engagement 4. Event 5. Reporting
Stage one - research/requirements
24.3 The project team was responsible for the full management and organisation of the event from its inception, including choosing the location and appropriate event date, identifying and managing suitable delegates and speakers, marketing and promoting the event, organising the event logistics, planning on-site details and liaising effectively with suppliers to organise EPDT merchandise.
24.4 Stage one involved establishing the requirements of the international conference which served as a ‘closing event’ for EPDT. The aims of the event were identified by the project team in consultation with the project board. The conference featured analysis outcomes of the project, the benefits and lessons learnt and discussions on developing the IT tool for stakeholders to adopt if they so choose.
24.5 The ‘lessons learnt’ from the EU funded ‘Improving Data Quality of EU Criminals’ (IDQEUC) project, which preceded the EPDT project, were considered and it became clear that holding the conference close to an international airport best suited the delegates and speakers.
24.6 London Heathrow was identified as the best location as a variety of good conference facilities were found nearby and the airport provided easy access for delegates.
24.7 A series of scoping visits where made to potential venues near to Heathrow including the Hilton, the Renaissance, the Sheraton Heathrow and the Park Inn.
24.8 A number of factors were considered including cost, internet speed (for presentation purposes), airport transfers, accessibility and general facilities and amenities. It was determined that the Park Inn offered the best value for money.
acro.police.uk 93 Stage two - procurement
24.9 Stage two naturally progressed on from the research aspect of work stream three. This stage focussed on the procurement of a conference venue.
24.10 The scoping exercise identified the Park Inn in Heathrow as the most suitable venue due to the locality of the hotel, its facilities and value for money.
24.11 A formal contract was agreed and signed. The contract was initially for 35 delegates which included: • Return flights to Heathrow, London • One night hotel accommodation, including breakfast • Conference dinner • Refreshments during the event
24.12 The project team subsequently engaged with each of the 27 EU MS (not including UK), and ascertained from email responses that the project team expected around 20 EU delegates to attend the conference.
24.13 With this in mind the project team requested the contract be amended from 35 to 28 delegates. The Park Inn supplied the new contract which was signed on 23rd August 2016.
24.14 The payment of the venue was subsequently verified by the EPDT Finance Officer.
Stage three - delegate engagement
24.15 This stage required the project team to further engage with delegates from EU MS to ascertain whether or not they wish to attend the EPDT project’s international conference.
24.16 On the 12th October 2016 invitations were sent to all MS Central Authorities. Delegates responded by email using a confirmation form designed by the project team, allowing their contact details, hotel and flight information to be collated and recorded on a spreadsheet to ensure that arrangements remained within the budget. Attendees were also asked to provide details of any specific needs, for instance specific dietary requirements; these were recorded and communicated to the Park Inn.
24.17 Two experts from EMCDDA were invited to speak at the conference as the EMCDDA is the central source and confirmed authority on drug-related issues in Europe. The agency has been collecting and analysing drugs data for a number of years and experienced similar challenges faced by the project team.
94 Criminal record analysis to support the European Pact on International Drug Trafficking 24.18 The project team booked the desired flights on behalf of all delegates. A set amount was budgeted for each flight and the project team researched different flights on each occasion to ensure that not only the flight times were suitable but also that the flight was best value for money. A spreadsheet of travel costs was created and any travel booked was input onto the spreadsheet to keep track of the budget and booking details.
24.19 The flight details and conference information was sent to each delegate at the beginning of January 2017.
Stage four - event
24.20 The conference took place on the 30th and 31st January 2017 in Heathrow, London with 22 delegates. The delegates represented 14 EU MS.
24.21 The conference was split over two days. This arrangement allowed for a conference dinner on the first day offering delegates the opportunity to network. The delivery of the conference presentation was on the second day. This second day was split into three sessions, in the first session the project team gave an overview of the project followed by a presentation from the ACRO ECRIS Manager, the second session centred on the findings of the EPDT Project, with the team demonstrating the Power BI tool and the final session centred on the work of EMCDDA.
24.22 The conference provided an excellent opportunity for the project team, invited speakers and delegates to share information and experience. The specific aims of the conference were to relay the findings of the project and to initiate discussion and debate on the use of ECRIS data.
24.23 In order to create a recognisable identity for the EPDT project conference, a picture graphic, colour scheme and logo was designed and used by the project team. The graphics were then incorporated into the production of the conference merchandise; conference banners, notepads, pens, stress cube and folders. This merchandise was given to each of the delegates to take back to their workplaces to generate interest and discussion around the EPDT project.
Stage five - reporting
24.24 Initial feedback from MS was very positive and constructive. It was identified that the EPDT Team should now approach the EU Commission, as well as Europol, Interpol and the National Crime Agency (NCA) to brief them on the IT tool and key findings in order to progress the project into a practical policing environment.
24.25 The project team are now in the process of engaging with such organisations in order to do this and hope to conduct a series of visits between February and March 2017.
acro.police.uk 95 24.26 After the conference the project team conducted a survey to retrieve feedback from the delegates that attended (Appendix J). The feedback obtained from delegates enabled the project team to evaluate the success of the project.
24.27 The feedback from the survey showed that the conference was deemed to be successful and the feedback has generally been positive. This was not only in relation to the venue in Heathrow and the organisation of the event by the EPDT project team, but also the use of the IT tool Power BI and speakers’ presentations and the topics that were discussed.
24.28 The results of the survey are still being gathered at the time of writing this report, however out of the 14 EU delegates who attended nine have replied. The majority plan on adopting the EPDT methodology when it comes to using the IT tool. Figure 24.1 provides an overview of some of the feedback received from delegates.
Figure 24.1 - Overview of feedback provided by EU conference delegates
Rating of topics (1 is the lowest score and 5 is the highest) 1 2 3 4 5
8
7
6
5
4
3
2
1
0
d d n ce ing an an tio n er rs s rs ra g re at ke n ke n ist kin nfe C ea tio a tio in oo o p nta pe nta ) m b C ue S se S e A Relevance to Ad ur n e ) es D yo ve pr O pr CD your workplace f CR M o (A (E
24.29 Feedback from one delegate highlighted that the ECRIS system holds only basic information on convictions in the EU but agreed that this information should be analysed. However, they noted that they can “hardly see extensions of such data. Quite the opposite trend is recently under discussion, especially with regard of data protection, subsidiarity, proportionality etc”.
96 Criminal record analysis to support the European Pact on International Drug Trafficking 24.30 Any constructive feedback has been taken on board by the EPDT team. This is something the EPDT project team have addressed and documented in the recommendations of this report and will also be discussing these points with the EU Commission moving forward.
24.31 In general, feedback was positive. The Lithuanian delegate stated “the Police has shown interest in using Power BI for data analysis. Lithuanian Criminal Police Bureau would use it for data analysis in order to improve engagement with drugs, prevention at the country”. A delegate from the EMCDDA fed back that “it was definitely extremely valuable for us to meet you and to find out more about ACRO and the EPDT project results. It was a great pleasure to attend such a well organised conference”.
24.32 The majority of delegates stated that they would benefit from using Power BI as an analytical tool and could see the value of analysing ECRIS data, with some delegates stating that it would be used for managing crime rates, analysing certain offences across the EU.
acro.police.uk 97 25 Forward look
25.1 On the 23rd June 2016, the referendum result showed a majority voting in favour of the UK leaving the EU. It is unknown whether Brexit will impact on the ability to exchange criminal records with EU MS. It is hoped that in the future, new negotiations will enable the UKCA-ECR to exchange criminal conviction information with the 27 MS. However, the impact will not be known until ‘Article 50’ is triggered by the end of March 2017, which sets a two year time limit for formal negotiation with the EU Commission setting the terms on which the UK will leave the EU.
25.2 Drug markets are not static, they are always evolving. The last decade has witnessed the emergence of a wide range of NPS.96 These drugs are designed to mimic the effects of established drugs which account for their ever increasing popularity and are easily accessible through the global marketplace of the internet. There is a significant threat from NPS as there is a lack of knowledge as to how widespread its use is and whether OCG are likely to become involved in supplying such drugs if the market is deemed profitable.97
25.3 Developments in internet markets including the Darknet offer new opportunities for online drug supply. The European Drug Report 2016 acknowledges the threat posed by new technologies such as the darknet. Europol and EMCDDA confirm that currently, these markets account for a small share of the illicit drugs trade market and report that many of the transactions occur at consumer level. However, the threat exists for further expansion of online trading.98
25.4 At the time of writing this report, the EU Commission are proposing to facilitate the exchange of criminal record of Non EU nationals in the EU by upgrading ECRIS. The EU Commission stated that “this initiative will ensure that ECRIS, which is already widely used for exchanging of criminal records of EU citizens, will be used to its full potential.” 99 This would move ECRIS beyond its current remit, which covers only EU citizens, and may well see the introduction of a centralised European database to hold information on convicted third country nationals. This could potentially widen the data captured to include Non EU nationals to provide an overall picture of the risks posed by FNO.
25.5 Europol’s Threat Assessment recognise container shipments as a prominent method of trafficking drugs and drug precursors destined for the EU.100 The expansion of Tangier in Morocco will provide further opportunities for sea freight trafficking destined for Europe.101
96 http://www.emcdda.europa.eu/system/files/publications/2637/TDAT16001ENN.pdf 97 https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/368583/NPSexpertReviewPanelReport.pdf 98 http://www.emcdda.europa.eu/system/files/publications/2637/TDAT16001ENN.pdf 99 http://europa.eu/rapid/press-release_IP-16-87_en.htm 100 Europol, OCTA 2011, “EU Organised Crime Threat Assessment” 101 http://www.globaltrademag.com/global-trade-daily/news/apm-terminals-announces-new-port-investment-in-morocco
98 Criminal record analysis to support the European Pact on International Drug Trafficking 25.6 Comparative analysis has been limited throughout the project as national criminal laws differ from country to country. The development of EMCDDA’s ‘International Crime Classification of Crime for Statistical Purposes’ (ICCS) may go some way to addressing comparability challenges arising from differences in country legislation internationally. It is a classification structure which assigns criminal offences to categories that have certain degree of similarity in relation to conceptual, analytical and policy areas.102 It will allow for consistency which will improve analytical capabilities at an international level.
25.7 It is possible that the number of Non EU nationals visiting the EU may increase due to the agreement made in December 2015 between the EU and some Non EU countries enabling national’s from visa free countries access to the Schengen states.103 Colombia is one of many countries that are able to travel visa free, which is reported to be because, “trust in visa applicants of both countries is on the rise, with low visa refusal rates; irregular migration is at relatively low levels; security of travel documents is sufficient; security threats have receded; organised crime groups are currently not assessed as a significant threat to the EU (with the exception of drug trafficking).”104 Schengen countries rely on border control to manage immigration. Due to the relative ease of travel, it is likely that the European drugs market may experience an increase in drugs trafficking particularly from those nationals from the drug producing countries that are able to travel visa free.
25.8 As a result of the EPDT Project, the UK has already identified the significant benefit of analysing ECRIS and national conviction information to support policing objectives to reduce the risk from serious organised crime. The project team provided a brief analysis for the UK International Serious and Organised Crime (ISOC) Board highlighting the benefits in utilising the UK ECRIS and national conviction information as an analytical data source and using Power BI to present the data to identify crime trends and potentially support operations in relation to Serious and Organised Crime, particularly in relation to Human Trafficking and Modern Slavery. The project team are now liaising with the National Crime Agency and Europol to discuss the potential benefits of Power BI and how analysing serious crime data held within ECRIS can support law enforcement activity against those involved in transnational and serious and organised crime.
102 https://www.unodc.org/unodc/en/data-and-analysis/statistics/iccs.html 103 https://ec.europa.eu/home-affairs/what-we-do/policies/borders-and-visas/visa-policy_en 104 http://europa.eu/rapid/press-release_IP-14-1208_en.htm acro.police.uk 99 26 Conclusion
26.1 Overall, the project has been successful in completing all of the activities and objectives with positive results. It is worth noting the three objectives of the project together with a summary for each objective.
To evaluate how criminal records across the EU can be utilised to support an EU pact on international drug trafficking.
26.2 This objective emanated from the current EU EMPACT cycle and the work of Europol and the European Council. On the 3rd June 2010 the Council of the EU agreed to a European pact to combat international drug trafficking initially focussed on disrupting cocaine and heroin drug trafficking routes.
26.3 This report highlights that organised criminal networks are international in scope and therefore a European-level response is required to make a difference in the pact against international drugs trafficking.
26.4 The pact requires cooperation from a broad range of agencies, including the police, MS Central Authorities, Judicial Authorities, Europol, Interpol, EMCDDA and UNODC as well a requirement to work in partnership with those source and transit countries that sit outside of Europe. In particular, EMCDDA has developed the infrastructure and tools needed to collect country data, to include law enforcement data from each MS in a harmonised way. Overall, these agencies produce an overview of the current state of the global drugs market and draw conclusions by combining agency information from multiple sources.
26.5 The EPDT project highlighted how criminal records, particularly ECRIS data could be utilised for intelligence purposes to combat the fight against international drug trafficking. ECRIS holds a wealth of information that could be used for identifying drug offending patterns throughout Europe. Examples include, analysis of offending histories based on nationality, age or gender as well as the potential to analyse a variety of fields that are populated within ECRIS which are optional rather than obligatory fields such as the location of the offence.
26.6 It was initially agreed in the project bid that the project team would aim to engage and retrieve data from 12 MS within the timeframe of the project. This was not achieved due partly to the protracted lengths of time it took to get agreement from specific MS and the limitations surrounding individual MS data and extraction capabilities.
100 Criminal record analysis to support the European Pact on International Drug Trafficking 26.7 In general, the data retrieval process was challenging, paticularly in relation to differences in legislation across Europe and retention guidelines set by each country. With the differences in how drug crime is recorded together with different interpretations of data protection it appeared that no two MS could supply a full set of comparable data. As a result, to identify the level of conviction for a specific drug type on a comparable level was therefore extremely difficult. However, this should not be seen as an obstacle not to consider further analysis.
26.8 The project team received datasets from nine MS which assisted in highlighting how ECRIS and national crime record data could be used for intelligence purposes to enhance law enforcement responses towards international drug trafficking. These datasets varied considerably in size, demographics and legal framework.
26.9 The project also acknowledged data limitations in respect to ECRIS connectivity, for example, Portugal is currently working on enabling exchange within ECRIS and both Malta and Slovenia are exchanging with only one other MS. It is important to note here that the full analytical benefits of analysing ECRIS data can only be recognised when all MS are connected.
26.10 Geographical analysis has identified some key trends which are presented in the individual country pages and key findings of this report. The project team were unable to utilise the ECRIS data for geographical analysis as ‘offence location’ is not typically exchanged between MS via ECRIS. The National data filled this gap and enabled the project team to map this data using the IT tool, Power BI. This provides the basis to the recommendations made for future consideration; to expand the categories of ‘obligatory’ information to include offence location under the Framework Decision therefore making it mandatory to exchange offence location within ECRIS rather than optional.
To identify a model that enables the analysis of criminal records to continue once the project expires. This model should also be flexible enough to be applicable to analysis of all forms of offending.
26.11 Having reviewed the system architecture for each MS in respect to ECRIS it became apparent that a common denominator was the Microsoft operating system. For this reason, the project team opted for a solution designed to work with Microsoft, a system called Power BI.
26.12 Power BI has the capability to work across a variety of ECRIS software applications and so it can assist in analysing criminal record data which can be used by EU MS if they desire to conduct analysis of their ECRIS data outside and beyond this project.
26.13 Power BI simplifies data discovery, access and collaboration and is available at little or no cost as the majority of EU MS have some form of Microsoft system built into their IT framework, although a specific version of Microsoft version is required; Excel 2013 (Office Professional Plus).
acro.police.uk 101 26.14 There are four components to Power BI:
• Power Query – this component allows you to connect to a variety of different data sources such as ECRIS, extract data from the source quickly and easily and provide steps to ‘clean’ the data before it gets loaded into Excel.
• Power Pivot – whereas, traditional PivotTables are limited to just one source table, Power Pivot allows the end user to create relationships between multiple data sources. This component also provides the capability to work with very large data volumes by using the Excel data model.
• Power View – provides more options for the end user to visualize the data by creating attractive, interactive dashboards and enables the end user to geographically map the data (if location details are available).
• Power Map – allows the end user to plot geographic data. Once this data is mapped, the end user has the capability to pan, zoom and display data over many locations. The end user can then analyse that data in 3D and create cinematic tours to share with others.
26.15 Power BI allowed for the efficient extraction of ECRIS data for the UK allowing for the project team to progress with the data analysis. The experiences of Power BI have been shared and with that the project team designed a demonstration model which was presented to all participating MS at each country visit. The project team found that the majority of MS who engaged in the project were positive about the use of Power BI as an analytical tool and could see the benefits of its use.
26.16 Power BI can now be utilised by all MS not only to analyse ECRIS and national data for drugs trafficking offences but to analyse other crime types and datasets, including those for the non EU nationals. This will assist MS in identifying threats and taking law enforcement action to mitigate this.
To identify how existing EU co-operations mechanisms can be enhanced by using criminal records to combat international drug trafficking.
26.17 This objective links back to developing a closer working relationship and a better understanding of the work of EMCDDA. At present each MS has to provide an annual report to the EMCDDA, a decentralised agency that exists to provide the EU and MS with a factual overview of the European drug situation.
26.18 The project highlights that a closer working relationship with or the developed analysis of EMCDDA data which incorporates ECRIS criminal conviction data may provide a more refined benefit to the EU pact over the forthcoming years.
102 Criminal record analysis to support the European Pact on International Drug Trafficking 26.19 The data collated by EMCDDA assists in informing and designing drug legislation and intervention strategies. As previously stated, they do not currently report on ECRIS conviction data but utilising this criminal record data and combining it with a business intelligence tool such as Power BI could provide additional assistance to EMCDDA and other government agencies.
26.20 Throughout this project there has been a degree of uncertainty when talking about patterns and trends in drug use across Europe due to the difference in legislation across the 28 MS but EMCDDA’s work around standardising the reporting protocols is progressing which may assist in the analysis of criminal records predominantly in Europe but also to the wider global community.
26.21 The project highlights that all 28 MS need to collaborate in the systematic collection of ECRIS data. The data collection process should require the cooperation of experts from different Central Authorities to allow for improved data extraction in relation to ECRIS and increase the shared knowledge regarding this area.
26.22 It should be concluded that ECRIS data in its current form is not a relevant indicator of how drugs are trafficked across Europe, however if used alongside multiple sources of data such as seizure data and intelligence reports then it can assist in informing a full picture of drugs offending throughout Europe.
26.23 Given that ECRIS is still very much in its infancy in respect of the data exchanged and the limited number of EU MS covered, this report has to be considered as a starting point to better understand how ECRIS data can be used as an analytical source.
acro.police.uk 103 27 Recommendations
27.1 The EU Commission to endorse the findings of the project and recommend to MS the opportunities and benefits to analyse ECRIS and national criminal conviction information to support law enforcement activity.
The project has identified there is potential significant benefit of analysing ECRIS and national criminal conviction information to identify crime trends and to support law enforcement activity to reduce the risk from serious organised crime of all types.
27.2 The EU Commission considers closer working with Europol to determine if the analysis of ECRIS data could be shared with Europol to support EMPACT.
The project has identified that the analysis of ECRIS data may support Europol in completing the SOCTA and direct European law enforcement activity against those involved in transnational serious and organised crime.
27.3 The EU Commission considers close working with the EMCDDA to share the analysis of ECRIS data to support the EU Drug Markets Report which in turn feeds in to EMPACT.
The project has identified through the analysis of ECRIS data and close working with EMCDDA during the project that the EMCDDA see a significant benefit of using drugs trafficking conviction data to complement the EU Drugs Market Report.
27.4 The EU Commission endorses and promotes to MS the use of Power BI for the analysis of ECRIS and national conviction information to identify crime trends within MS and support law enforcement activity.
The project has identified Microsoft Power BI as a powerful analytical tool to analyse, present and map bulk data extracted from ECRIS and national criminal conviction information. This could greatly assist law enforcement activity in EU MS targeting those involved in transnational serious and organised crime.
27.5 The EU Commission to consider obligating the ECRIS offence location field.
The Council Framework Decision 2009/315/JHA allows the optional recording of offence location. The project has identified that to enhance the quality of the analysis of ECRIS data the offence location field should be obligatory. This will ensure that the analysis and mapping of offences would be more accurate in presenting crime trends and supporting law enforcement activity against those involved in transnational and serious and organised crime.
104 Criminal record analysis to support the European Pact on International Drug Trafficking 28 Lessons Learnt
28.1 The project team recruitment was not started until after the project formally commenced. This impacted on the available time to set up and construct the required processes to commence the project.
On notification of a successful project bid the recruitment process should commence immediately. This would enable a smooth transition between the initial work stream of setting up the project and the commencement of formal work.
28.2 The appointment and selection of the Project Board did not commence until after the project started. This impacted on the ability to meet the EU requirements on the amount of meetings held and more importantly it required the board to make decisions on individual work stream commencement without the benefit of review.
On notification of a successful project bid the invitation and formation of the board should commence immediately.
28.3 The initial bid was conducted by a separate team and so the audit trail of how partners were co-opted onto the project was unclear. The expectations of the project were not clearly defined to the co-beneficiaries at the start of the project as the project team were unable to provenance the bid process.
All correspondence connected to the bid submission whether positive or negative should be available to the project team.
28.4 During the country visits, the project team identified that Germany delete their NO data after one year.
The questionnaire was largely focussed on the national criminal data register but it should have been designed to also contain questions relating to ECRIS and the associated retention guidelines for such data.
28.5 There has been a lack of support from the Hampshire/TVP IT department (external to ACRO) which made identifying suitable alternatives to Power BI difficult. The delay in waiting for assistance reached a point that in order to deliver against the project timescales the training for Power BI had to be delivered. In addition, for a long period of time there was insufficient IT resource available for the Intelligence Analyst which prohibited the analyst from performing the role.
Future projects should consider building in formal agreements regarding work carried out by Hampshire/ TVP IT department. acro.police.uk 105 28.6 There has been inconsistencies in relation to the management of the project, due to changes in personnel.
It is important to have the same project team for the duration of the project to allow for continuity and consistency.
28.7 The scope of the project was very ambitious and it was challenging with such a small project team to achieve all the objectives within the specified 24 month period. In particular, the analyst spent a significant amount of requesting data, ‘cleaning it’ by removing erroneous data and quality assuring the data. Ideally this role would have been undertaken by a researcher, however funding was not received for this post.
Consideration should be given as to whether the desired activities and objectives can be met and completed within the specified timescale with the available number of staff.
Future projects should ensure that appropriate number and range of staff are included for a project to be implemented.
28.8 At the start of the project, the project team attended a Prince2 course.
This provided the team with the necessary skills to run and manage the project from inception to completion.
28.9 It was useful for a member of the EPDT project team to attend the IDQEUC project conference.
This assisted the Project Support Officer with organising the EPDT project conference.
106 Criminal record analysis to support the European Pact on International Drug Trafficking 29 Appendix A - Connection matrix
Country AT BE BG CY CZ DE DK EE ES FI FR GB GR HR HU IE IT LT LU LV MT NL PL RO SE SI SK
AT 2013/04 2012/11 2014/09 2012/12 2012/04 2012/07 2012/05 2012/04 2012/08 2012/05 2012/04 2012/05 2013/07 2012/10 2012/10 2013/03 2012/04 2013/08 2012/08 2012/08 2012/04 2012/04 2013/06 2012/05
BE 2013/04 2013/02 2013/12 2013/02 2013/02 2013/04 2013/04 2013/02 2012/10 2013/01 2012/07 2014/04 2013/11 2013/02 2013/04 2013/04 2013/08 2013/06 2012/07 2013/02 2013/06 2013/06 2015/02
BG 2012/11 2013/02 2013/11 2013/06 2013/12 2013/07 2012/08 2013/02 2012/08 2013/01 2012/09 2013/09 2013/01 2013/02 2012/09 2013/08 2015/01 2012/07 2012/08 2012/11 2014/06
CY 2014/09 2013/12 2013/11 2014/10 2014/12 2014/08 2014/04 2013/03 2014/01 2014/06 2013/03 2014/06 2013/12 2013/11 2014/02 2013/09 2014/10 2015/01
CZ 2012/12 2013/02 2013/06 2014/10 2013/11 2013/12 2013/07 2012/04 2014/06 2013/01 2014/09 2013/11 2014/05 2013/02 2013/11 2014/04 2013/08 2014/08 2013/01 2012/12 2013/07 2014/04
DE 2012/04 2013/02 2013/12 2014/12 2013/11 2012/12 2014/07 2012/05 2014/03 2012/07 2012/05 2014/03 2014/02 2014/02 2013/07 2013/08 2013/11 2014/09 2013/12 2012/04 2014/02 2014/04 2015/02
DK 2012/07 2013/04 2013/07 2014/08 2013/12 2012/12 2012/07 2012/06 2013/09 2012/07 2013/11 2014/09 2013/07 2013/01 2013/11 2013/03 2013/08 2014/04 2012/04 2012/08 2013/07 2013/11 2014/12
EE 2012/05 2013/04 2012/08 2013/07 2014/07 2012/07 2012/04 2012/08 2012/05 2012/05 2013/04 2012/10 2013/04 2013/02 2013/09 2012/11 2013/02 2013/04 2015/01 2014/04 2015/01
ES 2012/04 2013/02 2013/02 2014/04 2012/04 2012/05 2012/06 2012/04 2012/05 2012/04 2012/05 2012/04 2013/11 2013/07 2012/04 2013/04 2012/06 2013/08 2014/05 2012/04 2012/05 2012/04 2013/12 2014/12
FI 2012/08 2012/10 2012/08 2014/06 2014/03 2013/09 2012/08 2012/08 2012/08 2012/09 2014/10 2014/12 2013/01 2014/05 2012/10 2013/10 2014/08 2012/08 2014/03 2013/01 2013/06 2015/01
FR 2012/05 2013/01 2013/01 2013/03 2013/01 2012/07 2012/07 2012/05 2012/04 2012/08 2012/05 2013/03 2014/05 2013/02 2013/02 2013/03 2012/05 2013/11 2014/11 2012/11 2012/05 2012/05 2014/05 2014/04
GB 2012/04 2012/07 2014/01 2012/05 2013/11 2012/05 2012/05 2012/09 2012/05 2012/09 2013/02 2013/01 2013/04 2012/05 2012/10 2012/10 2012/05 2012/05 2013/09 2015/01
GR 2012/05 2012/09 2014/06 2014/09 2014/09 2012/04 2013/03 2012/09 2013/03 2012/09 2012/05 2012/05 2014/10
HR 2013/07 2014/04 2013/11 2014/03 2013/11 2014/10 2014/05 2014/06 2015/01 2014/09 2014/09 2015/02 2014/05
HU 2012/10 2013/11 2013/09 2014/05 2014/02 2013/07 2013/04 2013/07 2014/12 2013/02 2013/02 2013/02 2014/04 2013/12 2013/08 2015/01 2014/08 2013/12 2015/01 2014/05
IE 2012/10 2013/02 2013/01 2013/03 2013/02 2014/02 2013/01 2012/10 2012/04 2013/01 2013/02 2013/01 2013/03 2014/06 2013/02 2012/12 2012/09 2012/10 2012/10 2013/01 2012/08 2013/12 2013/03
IT 2013/03 2013/04 2013/02 2014/06 2013/11 2013/07 2013/11 2013/04 2013/05 2014/05 2013/03 2013/04 2015/01 2014/04 2013/02 2013/10 2013/03 2013/04 2013/02 2013/03 2014/03 2015/01
LT 2012/05 2013/04 2012/09 2014/04 2013/08 2013/03 2013/02 2012/05 2012/10 2012/05 2012/05 2013/12 2012/12 2013/02 2013/08 2012/04 2012/07 2012/05 2012/11 2014/04 2014/04
LU 2013/08 2013/08 2013/08 2013/08 2013/11 2013/08 2013/09 2013/08 2013/10 2013/11 2013/08 2013/08 2013/09 2013/08 2014/08 2013/08 2013/09 2013/11 2014/08
LV 2012/08 2013/06 2015/01 2013/12 2014/08 2014/09 2014/04 2012/11 2014/05 2014/08 2014/11 2012/10 2015/01 2012/10 2013/03 2012/04 2014/08 2015/01 2012/07 2013/04 2013/02 2014/09
MT 2015/01
NL 2012/08 2012/07 2012/07 2013/11 2013/01 2013/12 2012/04 2013/02 2012/04 2012/08 2012/11 2012/10 2012/09 2014/09 2014/08 2012/10 2013/04 2012/07 2013/08 2012/07 2012/08 2012/07 2014/02
PL 2012/04 2013/02 2012/08 2014/02 2012/12 2012/05 2012/08 2013/04 2012/05 2014/03 2012/05 2012/05 2012/05 2014/09 2013/12 2013/01 2013/02 2012/05 2013/09 2013/04 2012/08 2012/05 2014/03
RO 2012/04 2013/06 2012/11 2013/09 2013/07 2014/02 2013/07 2015/01 2012/04 2012/11 2012/05 2012/05 2012/05 2015/02 2015/01 2012/08 2013/03 2012/11 2013/11 2013/02 2012/07 2012/05 2014/05
SE 2013/09 2013/10 2014/06 2014/10 2014/04 2014/04 2013/11 2014/04 2013/12 2014/02 2014/05 2013/09 2014/10 2014/05 2014/05 2013/12 2014/03 2014/04 2014/08 2014/09 2014/02 2014/03 2014/05 2015/01
SI 2014/04
SK 2012/06 2015/02 2015/01 2015/02 2014/12 2015/01 2014/12 2015/01 2014/04 2015/01 2013/03 2015/01 2015/01
acro.police.uk 107 30 Appendix B - ECRIS Process for Notifications Out (NO) and Notifications In (NI)
For a Notification Out (NO)
Subject convicted in the process will start at point 1 an EU Member State 1 and finish at point 5.
For a Notification In (NI) the
process will start at point 5 Conviction sent to and finish at point 6. 2 convicting Member
State’s criminal register
Conviction sent to
Member State’s
3 Central Authority for
the Exchange of
Criminal Records
Message with Message stating conviction details notification cannot be 4 sent to subject’s accepted sent to Member State(s) of convicting Member nationality Central State Authority
Central Authority of nationality acknowledges No receipt of notification or (if 5 not a national or cannot be found on the population register) rejects the notification
Yes
Member State of nationality updates 6 their criminal register with the conviction
acro.police.uk 108 31 Appendix C - QUEST search results against the 21 PNC ‘umbrella’ offence codes
PNC Codes Volume of PNC Records 9.1. 1650045 29.1. 124000 48.1. 27938 4.10.2. 22905 4.10.75. 6548 4.10.1. 6228 4.10.64. 2938 149.1. 2879 109.1. 1618 129. 1516 4.10.56. 1266 4.10.57. 885 4.10.59. 864 4.10.58 837 45.4. 578 9.4. 578 4.10.14. 485 4.10.63. 234 24.10.7. 74 29.2. 23 4.10.93. 8 1,852,447
109 Criminal record analysis to support the European Pact on International Drug Trafficking 32 Appendix D - QUEST search results against the 43 PNC ‘umbrella’
Volume of PNC PNC Offence Code PNC Offence Title Records 9.1.5.2 POSSESSING CONTROLLED DRUG - CLA SS A - COCA INE 184825 9.1.5.3 POSSESSING CONTROLLED DRUG - CLA SS A - HEROIN 109758 9.1.6.2 POSSESSING CONTROLLED DRUG W/I TO SUPPLY - CLA SS A - COCA INE 50843 9.1.6.3 POSSESSING CONTROLLED DRUG W/I TO SUPPLY - CLA SS A - HEROIN 49276 9.1.5.15 POSSESS A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 35533 9.1.4.3 SUPPLY ING CONTROLLED DRUG - CLA SS A - HEROIN 32280 9.1.6.15 POSSESS A CONTROLLED DRUG - W/I TO SUPPLY - CLA SS A - CRA CK COCA INE 22610 9.1.4.2 SUPPLY ING CONTROLLED DRUG - CLA SS A - COCA INE 20612 9.1.4.27 BEING CONCERNED IN SUPPLY ING CONTROLLED DRUG - CLA SS A - HEROIN 12601 9.1.4.51 SUPPLY A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 11051 9.1.4.26 BEING CONCERNED IN SUPPLY ING CONTROLLED DRUG - CLA SS A - COCA INE 7472 9.1.4.56 CONCERNED IN THE SUPPLY OF A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 3856 9.1.4.15 OFFERING TO SUPPLY CONTROLLED DRUG - CLA SS A - HEROIN 2095 9.1.4.14 OFFERING TO SUPPLY CONTROLLED DRUG - CLA SS A - COCA INE 1885 9.1.4.39 BEING CONCERNED IN OFFER TO SUPPLY CONTROLLED DRUG - CLA SS A - HEROIN 1403 9.1.4.38 BEING CONCERNED IN OFFER TO SUPPLY CONTROLLED DRUG - CLA SS A - COCA INE 1069 9.1.4.53 OFFER TO SUPPLY A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 753 9.1.8.3 PERMITTING PREMISES TO BE USED FOR SUPPLY ING CONTROLLED DRUG - CLA SS A - HEROIN 535 9.1.8.40 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - HEROIN 502 9.1.4.58 CONCERNED IN OFFER TO SUPPLY A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 327 9.1.8.2 PERMITTING PREMISES TO BE USED FOR SUPPLY ING CONTROLLED DRUG - CLA SS A - COCA INE 256 9.1.3.2 PRODUCING CONTROLLED DRUG - CLA SS A - COCA INE 240 9.1.8.42 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 231 9.1.8.41 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - COCA INE 222 9.1.3.14 BEING CONCERNED IN PRODUCING CONTROLLED DRUG - CLA SS A - COCA INE 200 9.1.3.15 BEING CONCERNED IN PRODUCING CONTROLLED DRUG - CLA SS A - HEROIN 138 9.1.3.25 PRODUCE A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 138 9.1.3.3 PRODUCING CONTROLLED DRUG - CLA SS A - HEROIN 119 9.1.3.28 CONCERNED IN THE PRODUCTION OF A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 92 9.1.8.25 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 63 9.1.9.6 PERMIT A DMINISTERING/USE OF DRUG ON PREMISES - CLA SS A - HEROIN 62 9.1.14.33 PERMITTING PRODUCTION OR A TTEMPTED PRODUCTION OF CONTROLLED DRUG ON PREMISES - CLA SS A - COCA INE 36 9.1.14.34 PERMITTING PRODUCTION OR A TTEMPTED PRODUCTION OF CONTROLLED DRUG ON PREMISES - CLA SS A - HEROIN 26 9.1.14.2 PERMITTING PREMISES TO BE USED FOR PRODUCING CONTROLLED DRUG - CLA SS A - COCA INE 23 9.1.8.15 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO SUPPLY CONTROLLED DRUG - CLA SS A - HEROIN 21 9.1.14.3 PERMITTING PREMISES TO BE USED FOR PRODUCING CONTROLLED DRUG - CLA SS A - HEROIN 15 9.1.8.14 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO SUPPLY CONTROLLED DRUG - CLA SS A - COCA INE 12 9.1.9.5 PERMIT A DMINISTERING / USE OF DRUG ON PREMISES - CLA SS A - COCA INE 8 9.1.8.28 PERMIT A TTEMPTED SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 6 9.1.14.25 PERMIT PRODUCTION OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 5 9.1.14.14 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO PRODUCE CONTROLLED DRUG - CLA SS A - COCA INE 1 9.1.14.15 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO PRODUCE CONTROLLED DRUG - CLA SS A - HEROIN 1 9.1.14.28 A TTEMPT TO PRODUCE CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 1
acro.police.uk 110 33 Appendix E - Questionnaire
In order to find out what criminal information each EU MS holds please can you assist us by answering the following questions (please answer in the answer box under each question):
Questionnaire completed by: Volume of PNC PNC Offence Code PNC Offence Title Records Name: 9.1.5.2 POSSESSING CONTROLLED DRUG - CLA SS A - COCA INE 184825 Job title: 9.1.5.3 POSSESSING CONTROLLED DRUG - CLA SS A - HEROIN 109758 9.1.6.2 POSSESSING CONTROLLED DRUG W/I TO SUPPLY - CLA SS A - COCA INE 50843 Contact details: 9.1.6.3 POSSESSING CONTROLLED DRUG W/I TO SUPPLY - CLA SS A - HEROIN 49276 9.1.5.15 POSSESS A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 35533 Questions / Answers Explanation of question 9.1.4.3 SUPPLY ING CONTROLLED DRUG - CLA SS A - HEROIN 32280 9.1.6.15 POSSESS A CONTROLLED DRUG - W/I TO SUPPLY - CLA SS A - CRA CK COCA INE 22610 9.1.4.2 SUPPLY ING CONTROLLED DRUG - CLA SS A - COCA INE 20612 Which agency(s) hold the criminal record information within For example, in the UK the police hold all criminal 9.1.4.27 BEING CONCERNED IN SUPPLY ING CONTROLLED DRUG - CLA SS A - HEROIN 12601 Q1 9.1.4.51 SUPPLY A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 11051 your country and who can access the information? record information. 9.1.4.26 BEING CONCERNED IN SUPPLY ING CONTROLLED DRUG - CLA SS A - COCA INE 7472 9.1.4.56 CONCERNED IN THE SUPPLY OF A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 3856 9.1.4.15 OFFERING TO SUPPLY CONTROLLED DRUG - CLA SS A - HEROIN 2095 9.1.4.14 OFFERING TO SUPPLY CONTROLLED DRUG - CLA SS A - COCA INE 1885 9.1.4.39 BEING CONCERNED IN OFFER TO SUPPLY CONTROLLED DRUG - CLA SS A - HEROIN 1403 9.1.4.38 BEING CONCERNED IN OFFER TO SUPPLY CONTROLLED DRUG - CLA SS A - COCA INE 1069 A1 9.1.4.53 OFFER TO SUPPLY A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 753 9.1.8.3 PERMITTING PREMISES TO BE USED FOR SUPPLY ING CONTROLLED DRUG - CLA SS A - HEROIN 535 9.1.8.40 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - HEROIN 502 9.1.4.58 CONCERNED IN OFFER TO SUPPLY A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 327 9.1.8.2 PERMITTING PREMISES TO BE USED FOR SUPPLY ING CONTROLLED DRUG - CLA SS A - COCA INE 256 9.1.3.2 PRODUCING CONTROLLED DRUG - CLA SS A - COCA INE 240 Is the criminal record information centrally held on a 9.1.8.42 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 231 9.1.8.41 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - COCA INE 222 database? If you have more than one criminal record database Q2 9.1.3.14 BEING CONCERNED IN PRODUCING CONTROLLED DRUG - CLA SS A - COCA INE 200 If so what is the name or identity of your criminal record please specify what they are called. 9.1.3.15 BEING CONCERNED IN PRODUCING CONTROLLED DRUG - CLA SS A - HEROIN 138 9.1.3.25 PRODUCE A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 138 database(s)? 9.1.3.3 PRODUCING CONTROLLED DRUG - CLA SS A - HEROIN 119 9.1.3.28 CONCERNED IN THE PRODUCTION OF A CONTROLLED DRUG - CLA SS A - CRA CK COCA INE 92 9.1.8.25 PERMIT SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 63 9.1.9.6 PERMIT A DMINISTERING/USE OF DRUG ON PREMISES - CLA SS A - HEROIN 62 9.1.14.33 PERMITTING PRODUCTION OR A TTEMPTED PRODUCTION OF CONTROLLED DRUG ON PREMISES - CLA SS A - COCA INE 36 9.1.14.34 PERMITTING PRODUCTION OR A TTEMPTED PRODUCTION OF CONTROLLED DRUG ON PREMISES - CLA SS A - HEROIN 26 A2 9.1.14.2 PERMITTING PREMISES TO BE USED FOR PRODUCING CONTROLLED DRUG - CLA SS A - COCA INE 23 9.1.8.15 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO SUPPLY CONTROLLED DRUG - CLA SS A - HEROIN 21 9.1.14.3 PERMITTING PREMISES TO BE USED FOR PRODUCING CONTROLLED DRUG - CLA SS A - HEROIN 15 9.1.8.14 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO SUPPLY CONTROLLED DRUG - CLA SS A - COCA INE 12 9.1.9.5 PERMIT A DMINISTERING / USE OF DRUG ON PREMISES - CLA SS A - COCA INE 8 Who specifically is in charge of the criminal record data 9.1.8.28 PERMIT A TTEMPTED SUPPLY OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 6 9.1.14.25 PERMIT PRODUCTION OF CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 5 and who would we need to contact in order to acquire Who would we need to talk to in order to acquire 9.1.14.14 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO PRODUCE CONTROLLED DRUG - CLA SS A - COCA INE 1 Q3 information to assist the project? sanitised data from your criminal record database? 9.1.14.15 PERMITTING PREMISES TO BE USED FOR A TTEMPTING TO PRODUCE CONTROLLED DRUG - CLA SS A - HEROIN 1 9.1.14.28 A TTEMPT TO PRODUCE CONTROLLED DRUG ON PREMISES - CLA SS A - CRA CK COCA INE 1 (name and e-mail address)
A3
111 Criminal record analysis to support the European Pact on International Drug Trafficking Questions / Answers Explanation of question
Are you able to specify what information your criminal record database holds? For example, the UK database (PNC) holds conviction and non-conviction information as well Can you supply a list of the data field headings that you Q4 as personal details about the offender. If you have populate with information? more than one criminal record database please specify what data each database holds. (Specifically does it include offence information and offence location?)
A4
Can you export information from your criminal record For example, can information be exported to Q5 database? If so in what format can you export the Microsoft Excel? data?
A5
Does your country routinely undertake any analysis on criminal record data? In the UK, we can analyse offending patterns on a national scale by exporting data from the PNC. Q6 If so who conducts the analysis? This helps us to identify trends in different types of Dept: offences. Name; Email address:
A6
acro.police.uk 112 Questions / Answers Explanation of question
If you do analyse data, how is it undertaken? (Please In order to identify drug trafficking patterns the describe the method or tool used to analyse the data Q7 EPDT project would like to utilise or replicate this as well as the strengths and weaknesses of the method process. or tool being used).
A7
For example, is it used to analyse offending patterns Q8 For what purpose is this analysis conducted? for the police or to provide statistical data for the Government.
A8
Would your agency be prepared to discuss sharing We are seeking support from eight EU MS in the Q9 relevant data or assisting this project with EU wide provision of data suitable for analysis analysis on drug trafficking?
A9
Is there any other information or assistance that your Q10 agency can provide which you may feel beneficial for the EPDT project?
A10
113 Criminal record analysis to support the European Pact on International Drug Trafficking 34 Appendix F - Data limitations
UK Notifications Out
This figure represents the number of notification messages sent by the UKCA-ECR to EU MS when one of their nationals is convicted in the UK, or a previous conviction is updated.
These figures include duplicate notifications, foreign convictions, non-convictions and cancellations which will not have been sent to EU MS.
ACRO does not hold information on all crimes committed in the UK by EU nationals. This information is only available from polices forces.
ACRO does not hold information on all convictions handed down against EU nationals in the UK. This information is only available from courts.
The destination member state is determined by the nationality as entered on the PNC record. This nationality can be self declared by the individual and therefore may not always be correct or truthful.
In 2011 and 2012 changes to Bichard 7 meant PNC was automatically updated when a case was adjourned or a person was remanded on bail. This resulted in the generation of a report to ACRO which appeared to be the result of the hearing and was therefore considered to be a conviction notification. Consequently, notification figures during this period were inflated. These notifications were amended and ceased being sent to ACRO by 2013.
A notification is deemed to contain convictions, or updates to convictions, and therefore may contain more than one offence.
UK Notifications In
This figure represents the number of notification messages received by the UKCA-ECR concerning UK nationals convicted in the EU and could also include updates to those convictions.
In 2013 both Ireland and Italy provided the UKCA-ECR with a large number of historical convictions for UK nationals.
Notifications are only sent to the UKCA-ECR when the subject declares their nationality as being UK and it is appropriately recorded as such in that MS. This self declaration could be incorrect or false; however, due to the UK not having a citizen register it is impossible to determine whether the subject of the notification is a true UK national.
acro.police.uk 114 Data Limitations - An Overview
For the majority of MS, the recording of drugs offences is dependent on police activities and priorities and is not a reliable indicator of the level of drug offending.
The project focussed on 2013 and 2014 conviction data. It is important to note that a number of MS were still not exchanging ECRIS data during this time and will therefore be underrepresented in the ECRIS data analysis. The national data assists in gilling this gap.
Each MS retrieved their ECRIS and national data information differently and so caution is required due to these differences in data collection methods. As a result, each MS dataset has its own set of caveats, as listed below:
UK – Not all cocaine (including crack) and heroin offences were included in the analysis as it is not possible to determine the drug type for all ‘Class A’ offences.
Spain – Offence address data was not available and so geographical analysis was conducted using the court address. This gives an approximate location as to where the offence occurred. However it should be noted that according to Spanish legislation, main cases of drug trafficking are judged at the Central Courts in Madrid which can firstly, potentially skew the data and secondly it may not identify all potential geographical hotspots.
Spain are also unable to provide drug type or distinguish between cultivation, possession or supply of drugs.
Lithuania – some of the Lithuania data required manual input by the Lithuanian CA, which potentially increases the possibility of data error. The quality assurance framework was implemented to ensure the datasets submitted were accurate and to a high standard.
Romania - unable to provide drug type or distinguish between cultivation, possession or supply of drugs.
The Romanian CA were unable to provide offence location and so the project team were unable to provide any geographical analysis
Germany – National data protection legislation resulted in Germany only sharing EU FNO data and as a result the project team were limited to the analysis of EU FNO.
Germany does not retain ECRIS NO data beyond its transmission. The provision of national data overcame this limitation.
115 Criminal record analysis to support the European Pact on International Drug Trafficking Data Limitations - An Overview continued
For Germany, offence address data was not available and so geographical analysis was conducted using the court address. This gives an approximate location as to where the offence occurred. However it should be noted that the ‘catchment’ can be large especially in cases where the deciding court was a regional court. Furthermore, there could be a few cases where the court address did not match the offence address as the authority of the local court did not meet the seriousness of the crime resulting in the offence being trialled at a regional court. This can firstly, potentially skew the data and secondly it may not identify all potential geographical hotspots.
Belgium – due to legislative constraints the Belgian CA were unable to distinguish between cultivation, possession and supply type offences.
Hungary – the dataset was very small making it difficult to find any significant data trends.
Hungarian legislation does not allow separate classification of offence by drug type nor does it classify between cultivation, possession or supply.
Croatia – were only able to provide six months of data for 2013 as Croatia only became operational on ECRIS in July 2013.
The Croatian CA were unable to provide offence location and so the project team were unable to provide any geographical analysis.
Italy – There were inconsistencies with the original dataset and in order to improve the quality of the data the project team manually ‘cleaned’ the data to improve the data quality. This should be considered when drawing conclusions about the findings of the Italian data.
acro.police.uk 116 35 Appendix G - Data requirement headings for Notifications In (NI)
Offence Nominal Data Offence Data Sanction Data Specifics
Box 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Number
Mapped Mapped Final Common Originating Place of Nationality Nationality Offence Offence Common National National Legal Mapped Conviction Sanction Sanction Title Sex DoB National Common Conviction Category Drug Type Country Birth 1 2 Address Description (MO) Category Code Title Provisions National Title Date Title Duration Code Category Date (Sanction)
Being Paseo de los Offences related to Trafficking in Concerned in Melancólicos, drugs or precursors, drugs serious Example London, Possession of Supplying O-00- Spain Female 18/10/1958 UK Unknown 77, 28005 and other offences 2190701 damage to the 368 CP 9.1.4.36 10/01/2014 14/04/2014 Imprisonment Imprisonment 2Y 6M Cocaine UK Cocaine Controlled 070300 Data Madrid, against public health (basic Drug - Class Spain health definition) not Specified
Data Heading Box Number Data Example Data Purpose Requirement for NI To analyse trends in relation to those countries submitting notifications into each Member State. For example, Spain may receive a larger number of notifications from Romania 1 Originating Country Spain in comparison to other Member States.
2 Sex Male/Female/Unknown To analyse trends on drugs conviction data in relation to gender
3 Date of Birth 18/10/1958 (DD/MM/YYYY) To analyse trends on drugs conviction data to show age ranges Nominal To analyse trends on drugs conviction data in relation to birth place. For example, do those born in London, UK have a propensity to commit crimes in France as opposed to 4 Place of Birth (Town/Country) London, UK offenders born elsewhere?
5 Nationality 1 UK To plot Nationality of convicted persons against a map of Europe to show trends of drug convictions across the EU. For example, this will allow the Analyst to highlight varying 6 Nationality 2 Unknown rates of criminality based on nationality.
7 Offence Address Paseo de los Melancólicos, 77, 28005 Madrid, Spain To enable the Analyst to plot offence location against a map of Europe to present the trends of drug convictions across the EU to identify patterns of offending and drug routes.
8 Offence Description (MO) Possession of Cocaine To determine whether the offence relates to the production, supply, possession or trafficking of drugs Offences related to drugs or precursors, and other offences against 9 Common Category (Offence) To utilise the ECRIS agreed European common categories of offences. This is required to analyse conviction type. public health The code of the offence as recorded on the national criminal register of the convicting Member State. This is the code under which the type of offence is identified in the 10 National Code 2190701 national judicial system of the convicting Member State. This is required to analyse conviction type.
11 National Title Trafficking in drugs serious damage to the health (basic definition) The title of the offence as known on the national level of the convicting Member State. This is required to analyse conviction type. Offence 12 Legal Provisions 368 CP The references to the articles of the national laws of the convicting Member State that have been breached. This is required to analyse conviction type.
Mapped National Code in 13 9.1.4.36 receiving MS On receipt of the notification in, the convictions are mapped to the MS equivalent offence. For example, in this case the Spanish offence has been mapped to the UK 14 Mapped National Title Being Concerned in Supplying Controlled Drug - Class not Specified equivalent. This is required to analyse conviction type.
15 Mapped Common Category O-00-070300
16 Conviction Date 27/08/2011 (DD/MM/YYYY) To ensure all data is within the project’s required date parameters
17 Final Conviction Date 21/10/2011 (DD/MM/YYYY) To ensure all data is within the project’s required date parameters
18 Common Category (Sanction) Imprisonment To utilise the ECRIS agreed European common categories of sanctions. This is required to analyse general trends in sentencing data
Sanction 19 National Title Imprisonment The title of the sanction as known on the national level of the convicting Member State. This is required to analyse general trends in sentencing data
20 Sanction Duration 2Y (years) 6M (Months) The duration of execution of the sanction, as sentenced by the deciding authority. This is required to analyse general trends in sentencing data Offence 21 Drug Type Cocaine This allows the EPDT team to specifically identify and therefore map the drug type. Specifics
acro.police.uk 117 Page 5 of 7 OFFICIAL 36 Appendix H - Data requirement headings for Notifications Out (NO)
Nominal Offence Sanction Offence Specifics Box 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Number
Final Common Place of Birth Nationality Nationality Offence Address / Offence Common National National Legal Conviction Sanction Sanction Title Sex DoB Conviction Category Drug Type (town/ country) 1 2 Postcode /Country Description / MO Category Code Title Provisions Date Title Duration Date (Sanction)
Trafficking in Offences related to Paseo de los drugs serious Example Possession of drugs or precursors, 2Y (Years) Female 18/10/1958 London, UK UK Unknown Melancólicos, 77, 2190701 damage to the 368 CP 10/01/2014 14/04/2014 Imprisonment Imprisonment Cocaine Cocaine and other offences 6M (Months) Data 28005 Madrid, Spain health (basic against public health definition)
Box Data Heading Data Example Data Purpose Number Requirement for NO
1 Sex Male/Female/Unknown To analyse trends on drugs conviction data in relation to gender 2 Date of Birth (DoB) 18/10/1958 (DD/MM/YYYY) To analyse trends on drugs conviction data to show age ranges
To analyse trends on drugs conviction data in relation to birth place. For example, do those born in London, UK have a propensity to commit crimes in France as Nominal 3 Place of Birth (Town/Country) London, UK opposed to offenders born elsewhere?
4 Nationality 1 UK To plot Nationality of convicted persons against a map of Europe to show trends of drug convictions across the EU. For example, this will allow the Analyst to 5 Nationality 2 Unknown highlight varying rates of criminality based on nationality. Paseo de los Melancólicos, 77, 28005 Madrid, Spain To enable the Analyst to plot offence location against a map of Europe to present the trends of drug convictions across the EU to identify patterns of offending 6 Offence Address and drug routes. 7 Offence Description / MO Possession of Cocaine To determine whether the offence relates to the production, supply, possession or trafficking of drugs
Offences related to drugs or precursors, and other offences against 8 Common Category (Offence) To utilise the ECRIS agreed European common categories of offences. This is required to analyse conviction type. public health
The code of the offence as known on the national level of the convicting Member State. This is the code under which the type of offence is identified in the Offence 9 National Code 2190701 national judicial system of the convicting Member State. This is required to analyse conviction type.
10 National Title Trafficking in drugs serious damage to the health (basic definition) The title of the offence as known on the national level of the convicting Member State. This is required to analyse conviction type. 11 Legal Provisions 368 CP The references to the articles of the national laws of the convicting Member State that have been breached. This is required to analyse conviction type. 12 Conviction Date 27/08/2011 (DD/MM/YYYY) To ensure all data is within the project’s required date parameters 13 Final Conviction Date 21/10/2011 (DD/MM/YYYY) To ensure all data is within the project’s required date parameters 14 Common Category (Sanction) Imprisonment To utilise the ECRIS agreed European common categories of sanctions. This is required to analyse general trends in sentencing data Sanction 15 National Title Imprisonment The title of the sanction as known on the national level of the convicting Member State. This is required to analyse general trends in sentencing data 16 Sanction Duration 2Y (years) 6M (Months) The duration of execution of the sanction, as sentenced by the deciding authority. This is required to analyse general trends in sentencing data Offence 17 Drug Type Cocaine This allows the EPDT team to specifically identify and therefore map the drug type. Specifics
118 Criminal record analysis to support the European Pact on International Drug Trafficking
Page 6 of 7 OFFICIAL 37 Appendix I - Power BI requirements
The EPDT project team established that for Microsoft Excel 2013 users Power BI is a free application if you have access to one of the following:
• A stand-alone version of Excel 2013 • An Office 2013 Professional Plus licence for your desktop • An Office 365 subscription that gives you access to the Office 2013 Professional Plus desktop tools
A full description of licencing details as well as links to install the various Power BI components can be found at https://powerbi.microsoft.com/.
If you have Microsoft Excel 2013 you can enable the add-in of Power BI by doing the following.
1. Open Excel 2013. 2. Click File and then Options. 3. Go down to the Add-Ins section on the left section of the Excel Options window. 4. At the bottom of the window is a drop down box named Manage, select COM Add-Ins and click Go. 5. A new window will open called COM Add-Ins. 6. Tick all the relevant Power BI products you wish to install and click OK. 7. If you selected all the available Power BI products you should now have Power Query and Power Pivot included on the ribbon at the top of your Excel data sheet. 8. Power View should be included on the Insert tab, (if this does not appear please email me as I have a potential work around that is too complex to include on this email).
Power Map requires a 64 bit base unit computer to operate.
Please note that some elements of Power BI require you to have data within your worksheet for it to operate.
The EPDT team received a training course on using Power BI, whilst this isn’t essential, it is recommended. Alternatively, there are many training demonstrations on how to use this IT on websites and video streaming services.
If you have any queries with the above please do not hesitate to contact the EPDT Team:
Email: [email protected]
acro.police.uk 119 38 Appendix J
1) Please indicate your overall satisfaction with this conference:
• Very satisfied • Somewhat satisfied • Neither satisfied nor dissatisfied • Dissatisfied • Very dissatisfied
2) Please rate these topics (1 is the lowest score and 5 the highest)
1 2 3 4 5
Speakers and presentations (ACRO)
Speakers and presentations (EMCDDA)
Relevance to your work
Administration of your booking
Conference venue
Catering
3) Do you think you would use Power BI in your place of work?
Yes/No
Comments:
4) How well do you think the Power BI product will meet your needs in the workplace?
• Extremely well • Very well • Well • Not so well • Not at all well
120 Criminal record analysis to support the European Pact on International Drug Trafficking 5) If you would use Power BI, what would you use it for? For example, would you use it to analyse ECRIS data or to assist in managing performance or resources? If you don’t intend to use Power BI, why not?
6) How likely are you to install Power BI at your workplace?
• Extremely likely • Very likely • Unsure • Not so likely • Not at all likely
7) Do you see value in analysing ECRIS data?
Comments
8) Are you likely to start analysing your own ECRIS data? If so, for what purpose?
9) The EPDT project identified that drug legislation varies significantly across EU Member States.
In your experience have you had any difficulties in mapping foreign offences into your own country legislation? If so, please explain what difficulties you have experienced.
10) Do you have any other comments or questions regarding the conference and its content?
Name of EPDT attendee (optional)
acro.police.uk 121 Supported by the Criminal Justice Programme of the European Union
ACRO, PO Box 481, Fareham, Hampshire, PO14 9FS [email protected] +44(0)1489 569800 acro.police.uk | @ACRO_Police ACRO Criminal Records Office